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  • 1.
    Aftab, Obaid
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Fryknäs, Mårten
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Hammerling, Ulf
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Larsson, Rolf
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Gustafsson, Mats
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Detection of cell aggregation and altered cell viability by automated label-free video microscopy: A promising alternative to endpoint viability assays in high throughput screening2015Inngår i: Journal of Biomolecular Screening, ISSN 1087-0571, E-ISSN 1552-454X, Vol. 20, nr 3, s. 372-381Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Automated phase-contrast video microscopy now makes it feasible to monitor a high-throughput (HT) screening experiment in a 384-well microtiter plate format by collecting one time-lapse video per well. Being a very cost-effective and label-free monitoring method, its potential as an alternative to cell viability assays was evaluated. Three simple morphology feature extraction and comparison algorithms were developed and implemented for analysis of differentially time-evolving morphologies (DTEMs) monitored in phase-contrast microscopy videos. The most promising layout, pixel histogram hierarchy comparison (PHHC), was able to detect several compounds that did not induce any significant change in cell viability, but made the cell population appear as spheroidal cell aggregates. According to recent reports, all these compounds seem to be involved in inhibition of platelet-derived growth factor receptor (PDGFR) signaling. Thus, automated quantification of DTEM (AQDTEM) holds strong promise as an alternative or complement to viability assays in HT in vitro screening of chemical compounds.

  • 2.
    Agarwal, Prasoon
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Hematologi och immunologi.
    Regulation of Gene Expression in Multiple Myeloma Cells and Normal Fibroblasts: Integrative Bioinformatic and Experimental Approaches2014Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    The work presented in this thesis applies integrative genomic and experimental approaches to investigate mechanisms involved in regulation of gene expression in the context of disease and normal cell biology.

    In papers I and II, we have explored the role of epigenetic regulation of gene expression in multiple myeloma (MM). By using a bioinformatic approach we identified the Polycomb repressive complex 2 (PRC2) to be a common denominator for the underexpressed gene signature in MM. By using inhibitors of the PRC2 we showed an activation of the genes silenced by H3K27me3 and a reduction in the tumor load and increased overall survival in the in vivo 5TMM model. Using ChIP-sequencing we defined the distribution of H3K27me3 and H3K4me3 marks in MM patients cells. In an integrated bioinformatic approach, the H3K27me3-associated genes significantly correlated to under-expression in patients with less favorable survival. Thus, our data indicates the presence of a common under-expressed gene profile and provides a rationale for implementing new therapies focusing on epigenetic alterations in MM.

    In paper III we address the existence of a small cell population in MM presenting with differential tumorigenic properties in the 5T33MM murine model. We report that the predominant population of CD138+ cells had higher engraftment potential, higher clonogenic growth, whereas the CD138- MM cells presented with less mature phenotype and higher drug resistance. Our findings suggest that while designing treatment regimes for MM, both the cellpopulations must be targeted.

    In paper IV we have studied the general mechanism of differential gene expression regulation by CGGBP1 in response to growth signals in normal human fibroblasts. We found that CGGBP1 binding affects global gene expression by RNA Polymerase II. This is mediated by Alu RNAdependentinhibition of RNA Polymerase II. In presence of growth signals CGGBP1 is retained in the nuclei and exhibits enhanced Alu binding thus inhibiting RNA Polymerase III binding on Alus. Hence we suggest a mechanism by which CGGBP1 orchestrates Alu RNA-mediated regulation of RNA Polymerase II. This thesis provides new insights for using integrative bioinformatic approaches to decipher gene expression regulation mechanisms in MM and in normal cells.

    Delarbeid
    1. Polycomb target genes are silenced in multiple myeloma
    Åpne denne publikasjonen i ny fane eller vindu >>Polycomb target genes are silenced in multiple myeloma
    Vise andre…
    2010 (engelsk)Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 5, nr 7, s. e11483-Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Multiple myeloma (MM) is a genetically heterogeneous disease, which to date remains fatal. Finding a common mechanism for initiation and progression of MM continues to be challenging. By means of integrative genomics, we identified an underexpressed gene signature in MM patient cells compared to normal counterpart plasma cells. This profile was enriched for previously defined H3K27-tri-methylated genes, targets of the Polycomb group (PcG) proteins in human embryonic fibroblasts. Additionally, the silenced gene signature was more pronounced in ISS stage III MM compared to stage I and II. Using chromatin immunoprecipitation (ChIP) assay on purified CD138+ cells from four MM patients and on two MM cell lines, we found enrichment of H3K27me3 at genes selected from the profile. As the data implied that the Polycomb-targeted gene profile would be highly relevant for pharmacological treatment of MM, we used two compounds to chemically revert the H3K27-tri-methylation mediated gene silencing. The S-adenosylhomocysteine hydrolase inhibitor 3-Deazaneplanocin (DZNep) and the histone deacetylase inhibitor LBH589 (Panobinostat), reactivated the expression of genes repressed by H3K27me3, depleted cells from the PRC2 component EZH2 and induced apoptosis in human MM cell lines. In the immunocompetent 5T33MM in vivo model for MM, treatment with LBH589 resulted in gene upregulation, reduced tumor load and increased overall survival. Taken together, our results reveal a common gene signature in MM, mediated by gene silencing via the Polycomb repressor complex. The importance of the underexpressed gene profile in MM tumor initiation and progression should be subjected to further studies.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-133207 (URN)10.1371/journal.pone.0011483 (DOI)000279715300003 ()20634887 (PubMedID)
    Tilgjengelig fra: 2010-11-03 Laget: 2010-11-03 Sist oppdatert: 2017-12-12bibliografisk kontrollert
    2. The epigenomic map of multiple myeloma reveals the importance of Polycomb gene silencing for the malignancy
    Åpne denne publikasjonen i ny fane eller vindu >>The epigenomic map of multiple myeloma reveals the importance of Polycomb gene silencing for the malignancy
    Vise andre…
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Multiple myeloma (MM) is characterized by accumulation of post-germinal center, isotype switched, long-living plasma cells with retained proliferation capacity within the bone marrow. MM is highly heterogeneous and remains fatal. This heterogeneity has hampered identification of a common underlying mechanism for disease establishment and the development of targeted therapy. We recently provided proof-of-principle that gene silencing associated with H3K27me3 contributes to the malignancy of MM. Here we present the first epigenomic map of MM for H3K27me3 and H3K4me3 derived by ChIP- and RNA sequencing from freshly-isolated bone marrow plasma cells from four patients. We compile lists of targets common among the patients as well as unique to MM when compared with PBMCs. Indicating the clinical relevance of our findings, we find increased silencing of H3K27me3 targets with disease progression and in patients presenting with a poor prognosis. Bivalent genes further significantly correlated to under-expressed genes in MM and were unique to MM when compared to PBMCs. Furthermore, bivalent genes, unlike H3K27me3 targets, significantly associated with transcriptional activation upon Polycomb inhibition indicating a potential for drug targeting. Thus, we suggest that gene silencing by Polycomb plays an important role in the development of the malignant phenotype of the MM cell during tumor progression.

    HSV kategori
    Forskningsprogram
    Onkologi
    Identifikatorer
    urn:nbn:se:uu:diva-199492 (URN)
    Tilgjengelig fra: 2013-05-06 Laget: 2013-05-06 Sist oppdatert: 2018-01-11bibliografisk kontrollert
    3. Tumor-initiating capacity of CD138- and CD138+ tumor cells in the 5T33 multiple myeloma model
    Åpne denne publikasjonen i ny fane eller vindu >>Tumor-initiating capacity of CD138- and CD138+ tumor cells in the 5T33 multiple myeloma model
    Vise andre…
    2012 (engelsk)Inngår i: Leukemia, ISSN 0887-6924, E-ISSN 1476-5551, Vol. 26, nr 6, s. 1436-1439Artikkel i tidsskrift, Letter (Fagfellevurdert) Published
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-177948 (URN)10.1038/leu.2011.373 (DOI)000305081000040 ()22289925 (PubMedID)
    Tilgjengelig fra: 2012-07-25 Laget: 2012-07-20 Sist oppdatert: 2017-12-07bibliografisk kontrollert
    4. Growth signals employ CGGBP1 to suppress transcription of Alu-SINEs
    Åpne denne publikasjonen i ny fane eller vindu >>Growth signals employ CGGBP1 to suppress transcription of Alu-SINEs
    Vise andre…
    2016 (engelsk)Inngår i: Cell Cycle, ISSN 1538-4101, E-ISSN 1551-4005, Vol. 15, nr 12, s. 1558-1571Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    CGGBP1 (CGG triplet repeat-binding protein 1) regulates cell proliferation, stress response,cytokinesis, telomeric integrity and transcription. It could affect these processes by modulatingtarget gene expression under different conditions. Identification of CGGBP1-target genes andtheir regulation could reveal how a transcription regulator affects such diverse cellular processes.Here we describe the mechanisms of differential gene expression regulation by CGGBP1 inquiescent or growing cells. By studying global gene expression patterns and genome-wide DNAbindingpatterns of CGGBP1, we show that a possible mechanism through which it affects theexpression of RNA Pol II-transcribed genes in trans depends on Alu RNA. We also show that itregulates Alu transcription in cis by binding to Alu promoter. Our results also indicate thatpotential phosphorylation of CGGBP1 upon growth stimulation facilitates its nuclear retention,Alu-binding and dislodging of RNA Pol III therefrom. These findings provide insights into howAlu transcription is regulated in response to growth signals.

    Emneord
    Alu-SINEs; CGGBP1; ChIP-seq; growth signals; RNA Pol III; transcription; tyrosine phosphorylation
    HSV kategori
    Forskningsprogram
    Bioinformatik; Biologi
    Identifikatorer
    urn:nbn:se:uu:diva-230959 (URN)10.4161/15384101.2014.967094 (DOI)000379743800011 ()25483050 (PubMedID)
    Forskningsfinansiär
    Swedish Cancer SocietySwedish Research Council
    Tilgjengelig fra: 2014-09-01 Laget: 2014-09-01 Sist oppdatert: 2017-12-05bibliografisk kontrollert
  • 3.
    Ahmed, Laeeq
    et al.
    Royal Institute of Technology, KTH.
    Georgiev, Valentin
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Capuccini, Marco
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Toor, Salman
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Schaal, Wesley
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Laure, Erwin
    Royal Institute of Technology, KTH.
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Efficient iterative virtual screening with Apache Spark and conformal prediction.2018Inngår i: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 10, artikkel-id 8Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND: Docking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands.

    CONTRIBUTION: In this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as 'low-scoring' ligands. Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached. Thereafter, the remaining ligands are docked or excluded based on this model. We use SVM and conformal prediction to deliver valid prediction intervals for ranking the predicted ligands, and Apache Spark to parallelize both the docking and the modeling.

    RESULTS: We show on 4 different targets that conformal prediction based virtual screening (CPVS) is able to reduce the number of docked molecules by 62.61% while retaining an accuracy for the top 30 hits of 94% on average and a speedup of 3.7. The implementation is available as open source via GitHub ( https://github.com/laeeq80/spark-cpvs ) and can be run on high-performance computers as well as on cloud resources.

  • 4.
    Ajawatanawong, Pravech
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för organismbiologi, Systematisk biologi.
    Atkinson, Gemma C.
    Watson-Haigh, Nathan S.
    MacKenzie, Bryony
    Baldauf, Sandra L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för organismbiologi, Systematisk biologi.
    SeqFIRE: a web application for automated extraction of indel regions and conserved blocks from protein multiple sequence alignments2012Inngår i: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 40, nr W1, s. W340-W347Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Analyses of multiple sequence alignments generally focus on well-defined conserved sequence blocks, while the rest of the alignment is largely ignored or discarded. This is especially true in phylogenomics, where large multigene datasets are produced through automated pipelines. However, some of the most powerful phylogenetic markers have been found in the variable length regions of multiple alignments, particularly insertions/deletions (indels) in protein sequences. We have developed Sequence Feature and Indel Region Extractor (SeqFIRE) to enable the automated identification and extraction of indels from protein sequence alignments. The program can also extract conserved blocks and identify fast evolving sites using a combination of conservation and entropy. All major variables can be adjusted by the user, allowing them to identify the sets of variables most suited to a particular analysis or dataset. Thus, all major tasks in preparing an alignment for further analysis are combined in a single flexible and user-friendly program. The output includes a numbered list of indels, alignments in NEXUS format with indels annotated or removed and indel-only matrices. SeqFIRE is a user-friendly web application, freely available online at www.seqfire.org/.

  • 5.
    Al-Jaff, Mohammed
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Sandström, Eric
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Grabherr, Manfred
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi. Uppsala Univ, Bioinformat Infrastruct Life Sci, S-75123 Uppsala, Sweden..
    microTaboo: a general and practical solution to the k-disjoint problem2017Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 18, artikkel-id 228Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: A common challenge in bioinformatics is to identify short sub-sequences that are unique in a set of genomes or reference sequences, which can efficiently be achieved by k-mer (k consecutive nucleotides) counting. However, there are several areas that would benefit from a more stringent definition of "unique", requiring that these sub-sequences of length W differ by more than k mismatches (i.e. a Hamming distance greater than k) from any other sub-sequence, which we term the k-disjoint problem. Examples include finding sequences unique to a pathogen for probe-based infection diagnostics; reducing off-target hits for re-sequencing or genome editing; detecting sequence (e.g. phage or viral) insertions; and multiple substitution mutations. Since both sensitivity and specificity are critical, an exhaustive, yet efficient solution is desirable.

    Results: We present microTaboo, a method that allows for efficient and extensive sequence mining of unique (k-disjoint) sequences of up to 100 nucleotides in length. On a number of simulated and real data sets ranging from microbe-to mammalian-size genomes, we show that microTaboo is able to efficiently find all sub-sequences of a specified length W that do not occur within a threshold of k mismatches in any other sub-sequence. We exemplify that microTaboo has many practical applications, including point substitution detection, sequence insertion detection, padlock probe target search, and candidate CRISPR target mining.

    Conclusions: microTaboo implements a solution to the k-disjoint problem in an alignment-and assembly free manner. microTaboo is available for Windows, Mac OS X, and Linux, running Java 7 and higher, under the GNU GPLv3 license, at:https://MohammedAlJaff.github.io/microTaboo

  • 6.
    Alvarsson, Jonathan
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Eklund, Martin
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Engkvist, Ola
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Carlsson, Lars
    Wikberg, Jarl E. S.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Noeske, Tobias
    Ligand-Based Target Prediction with Signature Fingerprints2014Inngår i: Journal of Chemical Information and Modeling, ISSN 1549-9596, Vol. 54, nr 10, s. 2647-2653Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When evaluating a potential drug candidate it is desirable to predict target interactions in silico prior to synthesis in order to assess, e.g., secondary pharmacology. This can be done by looking at known target binding profiles of similar compounds using chemical similarity searching. The purpose of this study was to construct and evaluate the performance of chemical fingerprints based on the molecular signature descriptor for performing target binding predictions. For the comparison we used the area under the receiver operating characteristics curve (AUC) complemented with net reclassification improvement (NRI). We created two open source signature fingerprints, a bit and a count version, and evaluated their performance compared to a set of established fingerprints with regards to predictions of binding targets using Tanimoto-based similarity searching on publicly available data sets extracted from ChEMBL. The results showed that the count version of the signature fingerprint performed on par with well-established fingerprints such as ECFP. The count version outperformed the bit version slightly; however, the count version is more complex and takes more computing time and memory to run so its usage should probably be evaluated on a case-by-case basis. The NRI based tests complemented the AUC based ones and showed signs of higher power.

  • 7.
    Alvarsson, Jonathan
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Lampa, Samuel
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Schaal, Wesley
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Andersson, Claes
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Wikberg, Jarl E. S.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Large-scale ligand-based predictive modelling using support vector machines2016Inngår i: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 8, artikkel-id 39Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse.

  • 8.
    Ameur, Adam
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Centrum för bioinformatik.
    A Bioinformatics Study of Human Transcriptional Regulation2008Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Regulation of transcription is a central mechanism in all living cells that now can be investigated with high-throughput technologies. Data produced from such experiments give new insights to how transcription factors (TFs) coordinate the gene transcription and thereby regulate the amounts of proteins produced. These studies are also important from a medical perspective since TF proteins are often involved in disease. To learn more about transcriptional regulation, we have developed strategies for analysis of data from microarray and massively parallel sequencing (MPS) experiments.

    Our computational results consist of methods to handle the steadily increasing amount of data from high-throughput technologies. Microarray data analysis tools have been assembled in the LCB-Data Warehouse (LCB-DWH) (paper I), and other analysis strategies have been developed for MPS data (paper V). We have also developed a de novo motif search algorithm called BCRANK (paper IV).

    The analysis has lead to interesting biological findings in human liver cells (papers II-V). The investigated TFs appeared to bind at several thousand sites in the genome, that we have identified at base pair resolution. The investigated histone modifications are mainly found downstream of transcription start sites, and correlated to transcriptional activity. These histone marks are frequently found for pairs of genes in a bidirectional conformation. Our results suggest that a TF can bind in the shared promoter of two genes and regulate both of them.

    From a medical perspective, the genes bound by the investigated TFs are candidates to be involved in metabolic disorders. Moreover, we have developed a new strategy to detect single nucleotide polymorphisms (SNPs) that disrupt the binding of a TF (paper IV). We further demonstrated that SNPs can affect transcription in the immediate vicinity. Ultimately, our method may prove helpful to find disease-causing regulatory SNPs.

    Delarbeid
    1. The LCB Data Warehouse
    Åpne denne publikasjonen i ny fane eller vindu >>The LCB Data Warehouse
    Vise andre…
    2006 (engelsk)Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 22, nr 8, s. 1024-1026Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    The Linnaeus Centre for Bioinformatics Data Warehouse (LCB-DWH) is a web-based infrastructure for reliable and secure microarray gene expression data management and analysis that provides an online service for the scientific community. The LCB-DWH is an effort towards a complete system for storage (using the BASE system), analysis and publication of microarray data. Important features of the system include: access to established methods within R/Bioconductor for data analysis, built-in connection to the Gene Ontology database and a scripting facility for automatic recording and re-play of all the steps of the analysis. The service is up and running on a high performance server. At present there are more than 150 registered users.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-97704 (URN)10.1093/bioinformatics/btl036 (DOI)16455749 (PubMedID)
    Tilgjengelig fra: 2008-11-06 Laget: 2008-11-06 Sist oppdatert: 2017-12-14bibliografisk kontrollert
    2. Binding sites for metabolic disease related transcription factors inferred at base pair resolution by chromatin immunoprecipitation and genomic microarrays
    Åpne denne publikasjonen i ny fane eller vindu >>Binding sites for metabolic disease related transcription factors inferred at base pair resolution by chromatin immunoprecipitation and genomic microarrays
    Vise andre…
    2005 (engelsk)Inngår i: Human Molecular Genetics, ISSN 0964-6906, E-ISSN 1460-2083, Vol. 14, nr 22, s. 3435-3447Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    We present a detailed in vivo characterization of hepatocyte transcriptional regulation in HepG2 cells, using chromatin immunoprecipitation and detection on PCR fragment-based genomic tiling path arrays covering the encyclopedia of DNA element (ENCODE) regions. Our data suggest that HNF-4α and HNF-3β, which were commonly bound to distal regulatory elements, may cooperate in the regulation of a large fraction of the liver transcriptome and that both HNF-4α and USF1 may promote H3 acetylation to many of their targets. Importantly, bioinformatic analysis of the sequences bound by each transcription factor (TF) shows an over-representation of motifs highly similar to the in vitro established consensus sequences. On the basis of these data, we have inferred tentative binding sites at base pair resolution. Some of these sites have been previously found by in vitro analysis and some were verified in vitro in this study. Our data suggests that a similar approach could be used for the in vivo characterization of all predicted/uncharacterized TF and that the analysis could be scaled to the whole genome.

    Emneord
    Base Pairing/*genetics, Binding Sites/genetics, Cell Line; Tumor, Chromatin/*metabolism, Chromatin Immunoprecipitation/methods, Consensus Sequence, Genome; Human, Hepatocyte Nuclear Factor 3-beta/physiology, Hepatocyte Nuclear Factor 4/physiology, Hepatocytes/metabolism, Histones/metabolism, Humans, Metabolic Diseases/*metabolism, Oligonucleotide Array Sequence Analysis/methods, Promoter Regions (Genetics), Research Support; N.I.H.; Extramural, Research Support; Non-U.S. Gov't, Sequence Analysis; DNA, Transcription Factors/genetics/*metabolism, Upstream Stimulatory Factors/metabolism
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-80603 (URN)10.1093/hmg/ddi378 (DOI)16221759 (PubMedID)
    Tilgjengelig fra: 2006-05-19 Laget: 2006-05-19 Sist oppdatert: 2017-12-14bibliografisk kontrollert
    3. Whole-genome maps of USF1 and USF2 binding and histone H3 acetylation reveal new aspects of promoter structure and candidate genes for common human disorders
    Åpne denne publikasjonen i ny fane eller vindu >>Whole-genome maps of USF1 and USF2 binding and histone H3 acetylation reveal new aspects of promoter structure and candidate genes for common human disorders
    Vise andre…
    2008 (engelsk)Inngår i: Genome Research, ISSN 1088-9051, E-ISSN 1549-5469, Vol. 18, nr 3, s. 380-392Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Transcription factors and histone modifications are crucial regulators of gene expression that mutually influence each other. We present the DNA binding profiles of upstream stimulatory factors 1 and 2 (USF1, USF2) and acetylated histone H3 (H3ac) in a liver cell line for the whole human genome using ChIP-chip at a resolution of 35 base pairs. We determined that these three proteins bind mostly in proximity of protein coding genes transcription start sites (TSSs), and their bindings are positively correlated with gene expression levels. Based on the spatial and functional relationship between USFs and H3ac at protein coding gene promoters, we found similar promoter architecture for known genes and the novel and less-characterized transcripts human mRNAs and spliced ESTs. Furthermore, our analysis revealed a previously underestimated abundance of genes in a bidirectional conformation, where USFs are bound in between TSSs. After taking into account this promoter conformation, the results indicate that H3ac is mainly located downstream of TSS, and it is at this genomic location where it positively correlates with gene expression. Finally, USF1, which is associated to familial combined hyperlipidemia, was found to bind and potentially regulate nuclear mitochondrial genes as well as genes for lipid and cholesterol metabolism, frequently in collaboration with GA binding protein transcription factor alpha (GABPA, nuclear respiratory factor 2 [NRF-2]). This expands our understanding about the transcriptional control of metabolic processes and its alteration in metabolic disorders.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-97706 (URN)10.1101/gr.6880908 (DOI)000253766700004 ()18230803 (PubMedID)
    Tilgjengelig fra: 2008-11-06 Laget: 2008-11-06 Sist oppdatert: 2017-12-14bibliografisk kontrollert
    4. New algorithm and ChIP-analysis identifies candidate functional SNPs
    Åpne denne publikasjonen i ny fane eller vindu >>New algorithm and ChIP-analysis identifies candidate functional SNPs
    Vise andre…
    Inngår i: PNASArtikkel i tidsskrift (Fagfellevurdert) Submitted
    Identifikatorer
    urn:nbn:se:uu:diva-97707 (URN)
    Tilgjengelig fra: 2008-11-06 Laget: 2008-11-06bibliografisk kontrollert
    5. Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq
    Åpne denne publikasjonen i ny fane eller vindu >>Differential binding and co-binding pattern of FOXA1 and FOXA3 and their relation to H3K4me3 in HepG2 cells revealed by ChIP-seq
    Vise andre…
    2009 (engelsk)Inngår i: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, nr 11, s. R129-Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    BACKGROUND: The forkhead box/winged helix family members FOXA1, FOXA2, and FOXA3 are of high importance in development and specification of the hepatic linage and the continued expression of liver-specific genes. RESULTS: Here, we present a genome-wide location analysis of FOXA1 and FOXA3 binding sites in HepG2 cells through chromatin immunoprecipitation with detection by sequencing (ChIP-seq) studies and compare these with our previous results on FOXA2. We found that these factors often bind close to each other in different combinations and consecutive immunoprecipitation of chromatin for one and then a second factor (ChIP-reChIP) shows that this occurs in the same cell and on the same DNA molecule, suggestive of molecular interactions. Using co-immunoprecipitation, we further show that FOXA2 interacts with both FOXA1 and FOXA3 in vivo, while FOXA1 and FOXA3 do not appear to interact. Additionally, we detected diverse patterns of trimethylation of lysine 4 on histone H3 (H3K4me3) at transcriptional start sites and directionality of this modification at FOXA binding sites. Using the sequence reads at polymorphic positions, we were able to predict allele specific binding for FOXA1, FOXA3, and H3K4me3. Finally, several SNPs associated with diseases and quantitative traits were located in the enriched regions. CONCLUSIONS: We find that ChIP-seq can be used not only to create gene regulatory maps but also to predict molecular interactions and to inform on the mechanisms for common quantitative variation.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-119751 (URN)10.1186/gb-2009-10-11-r129 (DOI)000273344600016 ()19919681 (PubMedID)
    Merknad

    De två (2) första författarna delar förstaförfattarskapet.

    Tilgjengelig fra: 2010-03-01 Laget: 2010-03-01 Sist oppdatert: 2017-12-12bibliografisk kontrollert
  • 9.
    Amrein, Beat Anton
    et al.
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi.
    Steffen-Munsberg, Fabian
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Szeler, Ireneusz
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi.
    Purg, Miha
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Kulkarni, Yashraj
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Kamerlin, Shina Caroline Lynn
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Struktur- och molekylärbiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    CADEE: Computer-Aided Directed Evolution of Enzymes2017Inngår i: IUCrJ, ISSN 0972-6918, E-ISSN 2052-2525, Vol. 4, nr 1, s. 50-64Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The tremendous interest in enzymes as biocatalysts has led to extensive work in enzyme engineering, as well as associated methodology development. Here, a new framework for computer-aided directed evolution of enzymes (CADEE) is presented which allows a drastic reduction in the time necessary to prepare and analyze in silico semi-automated directed evolution of enzymes. A pedagogical example of the application of CADEE to a real biological system is also presented in order to illustrate the CADEE workflow.

  • 10.
    Anslan, Sten
    et al.
    Braunschweig Univ Technol, Zool Inst, Mendelssohnstr 4, D-38106 Braunschweig, Germany.
    Nilsson, R. Henrik
    Univ Gothenburg, Dept Biol & Environm Sci, Gothenburg Global Biodivers Ctr, Box 461, S-40530 Gothenburg, Sweden.
    Wurzbacher, Christian
    Tech Univ Munich, Coulombwall 3, D-85748 Garching, Germany.
    Baldrian, Petr
    Czech Acad Sci, Inst Microbiol, Videnska 1083, Prague 14220 4, Czech Republic.
    Tedersoo, Leho
    Tartu Univ, Nat Hist Museum, 14a Ravila, Tartu 50411, Estonia.
    Bahram, Mohammad
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för organismbiologi, Systematisk biologi. Tartu Univ, Inst Ecol & Earth Sci, 14a Ravila, EE-50411 Tartu, Estonia;Swedish Univ Agr Sci, Dept Ecol, Ulls Vag 16, S-75651 Uppsala, Sweden.
    Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding2018Inngår i: MycoKeys, ISSN 1314-4057, E-ISSN 1314-4049, nr 39, s. 29-40Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

  • 11.
    Arvidsson, Staffan
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Carlsson, Lars
    AstraZeneca R&D.
    Paulo, Toccaceli
    Royal Holloway University of London.
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors2017Inngår i: Conformal and Probabilistic Prediction with Applications (COPA) 2017 / [ed] Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, Harris Papadopoulos, 2017, Vol. 60, s. 118-131Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Prediction of drug metabolism is an important topic in the drug discovery process, and we here present a study using probabilistic predictions applying Cross Venn-ABERS Predictors (CVAPs) on data for site-of-metabolism. We used a dataset of 73599 biotransformations, applied SMIRKS to define biotransformations of interest and constructed five datasets where chemical structures were represented using signatures descriptors. The results show that CVAP produces well-calibrated predictions for all datasets with good predictive capability, making CVAP an interesting method for further exploration in drug discovery applications.

  • 12.
    Attwood, T.K.
    et al.
    Faculty of Life Sciences & School of Computer Science, University of Manchester.
    Gisel, A
    Institute for Biomedical Technologies, CNR, Italy.
    Eriksson, Nils-Einar
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi.
    Bongcam-Rudloff, Erik
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences.
    Concepts, Historical Milestones and the Central Place of Bioinformatics in Modern Biology: A European Perspective2011Inngår i: Bioinformatics: Trends and Methodologies / [ed] Mahmood A. Mahdavi, InTech, 2011, s. 3-26Kapittel i bok, del av antologi (Fagfellevurdert)
  • 13.
    Austin, Peter C.
    et al.
    Inst Clin Evaluat Sci, G106,2075 Bayview Ave, Toronto, ON M4N 3M5, Canada.;Univ Toronto, Inst Hlth Management Policy & Evaluat, Toronto, ON, Canada.;Sunnybrook Res Inst, Schulich Heart Res Program, Toronto, ON, Canada..
    Wagner, Philippe
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska och farmaceutiska vetenskapsområdet, centrumbildningar mm, Centrum för klinisk forskning, Västerås. Lund Univ, Unit Social Epidemiol, Fac Med, Malmo, Sweden..
    Merlo, Juan
    Lund Univ, Unit Social Epidemiol, Fac Med, Malmo, Sweden.;Region Skane, Ctr Primary Hlth Care Res, Malmo, Sweden..
    The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis2017Inngår i: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 36, nr 6, s. 928-938Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis.

  • 14.
    Ballante, Flavio
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi.
    Protein-Ligand Docking in Drug Design: Performance Assessment and Binding-Pose Selection2018Inngår i: Rational Drug Design: Methods and Protocols / [ed] Thomas Mavromoustakos; Tahsin F. Kellici, New York, NY: Humana Press, 2018, s. 67-88Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    Main goal in drug discovery is the identification of drug-like compounds capable to modulate specific biological targets. Thus, the prediction of reliable binding poses of candidate ligands, through molecular docking simulations, represents a key step to be pursued in structure-based drug design (SBDD). Since the increasing number of resolved three-dimensional ligand-protein structures, together with the expansion of computational power and software development, the comprehensive and systematic use of experimental data can be proficiently employed to validate the docking performance. This allows to select and refine the protocol to adopt when predicting the binding pose of trial compounds in a target. Given the availability of multiple docking software, a comparative docking assessment in an early research stage represents a must-use step to minimize fails in molecular modeling. This chapter describes how to perform a docking assessment, using freely available tools, in a semiautomated fashion.

  • 15.
    Baltzer, Nicholas
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm County, Sweden.
    Sundström, Karin
    Karolinska Inst, Dept Lab Med, Stockholm, Stockholm Count, Sweden..
    Nygård, Jan F.
    Canc Registry Norway, Dept Registry Informat, Oslo, Oslo County, Norway..
    Dillner, Joakim
    Karolinska Inst, Dept Lab Med, Stockholm, Stockholm Count, Sweden..
    Komorowski, Jan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik. Polish Acad Sci, Inst Comp Sci, Warsaw, Warsaw County, Poland..
    Risk stratification in cervical cancer screening by complete screening history: Applying bioinformatics to a general screening population2017Inngår i: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 141, nr 1, s. 200-209Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Women screened for cervical cancer in Sweden are currently treated under a one-size-fits-all programme, which has been successful in reducing the incidence of cervical cancer but does not use all of the participants' available medical information. This study aimed to use women's complete cervical screening histories to identify diagnostic patterns that may indicate an increased risk of developing cervical cancer. A nationwide case-control study was performed where cervical cancer screening data from 125,476 women with a maximum follow-up of 10 years were evaluated for patterns of SNOMED diagnoses. The cancer development risk was estimated for a number of different screening history patterns and expressed as Odds Ratios (OR), with a history of 4 benign cervical tests as reference, using logistic regression. The overall performance of the model was moderate (64% accuracy, 71% area under curve) with 61-62% of the study population showing no specific patterns associated with risk. However, predictions for high-risk groups as defined by screening history patterns were highly discriminatory with ORs ranging from 8 to 36. The model for computing risk performed consistently across different screening history lengths, and several patterns predicted cancer outcomes. The results show the presence of risk-increasing and risk-decreasing factors in the screening history. Thus it is feasible to identify subgroups based on their complete screening histories. Several high-risk subgroups identified might benefit from an increased screening density. Some low-risk subgroups identified could likely have a moderately reduced screening density without additional risk.

  • 16.
    Baltzer, Nicholas
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik.
    Sundström, Karin
    Karolinska Inst, Dept Lab Med, Stockholm, Sweden.
    Nygård, Jan
    Canc Registry Norway, Dept Registry Informat, Oslo, Norway.
    Nygård, Mari
    Canc Registry Norway, Dept Registry Informat, Oslo, Norway.
    Dillner, Joakim
    Karolinska Inst, Dept Lab Med, Stockholm, Sweden.
    Komorowski, Jan
    Uppsala Univ, Dept Cell & Mol Biol, Uppsala, Sweden;Polish Acad Sci, Warsaw, Poland.
    Stratifying Cervical Cancer Risk With Registry Data2018Inngår i: 2018 IEEE 14th International Conference on e-Science (e-Science 2018), IEEE, 2018, s. 288-289Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The cervical cancer screening programmes in Sweden and Norway have successfully reduced the frequency of cervical cancer incidence but have not implemented any form of evaluation for screening needs. This means that the screening frequency for individuals can he suboptimal, increasing either the cost of the programme or the risk of missing an early stage cancer development. We developed a framework for assessing an individual's risk of cervical cancer based on their available screening history and computing a primary risk factor called CRS from a data-driven separation model together with multiple derived attributes. The results show that this approach is highly practical, validates against multiple established trends, and can he effective in personalizing the screening needs for individuals.

  • 17.
    Bampalikis, Dimitrios
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för biologisk grundutbildning.
    Recognizing biological and technical differences in scRNAseq: A comparison of two protocols2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Recent advances in sequencing technology have given access to information extracted on a single cell level. Single cell RNA sequencing enables for transcriptomes to be sequenced, allowing for studies within and between cell types. A recently developed protocol, based on Smart-seq2, and the Proximity ligation essay, allows for the detection of protein data from single cells, in parallel with RNA. The combination of the transcriptomic and proteomic data will enhance researchers’ ability to explore cell states. In this study, we are comparing a new pulldown protocol with the widely-used Smart-seq2, as well as against FACS sorted cells. Our results show differences in the RNA sequenced between the two protocols, as well the prediction of cell cycle state based on their data. Using RNA extracted from the pulldown protocol in different time points, we also calculate the direction of development for the cells. We expect that the incorporation of proteomic data will shed light to relevant biological questions related to the cell function.

  • 18. Barros, M
    et al.
    Dey, Subhrakanti
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Signaler och System.
    Feed-forward and feedback control in astrocytes for Ca2+-based molecular communications nanonetworks2018Inngår i: IEEE/ACM Transactions on Computational Biology & Bioinformatics, ISSN 1545-5963, E-ISSN 1557-9964Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Synaptic plasticity depends on the gliotransmitters' concentration in the synaptic channel. And, an abnormal concentration of gliotransmitters is linked to neurodegenerative diseases, including Alzheimer's, Parkinson's, and epilepsy. In this paper, a theoretical investigation of the cause of the abnormal concentration of gliotransmitters and how to achieve its control is presented through a Ca2+-signalling-based molecular communications framework. A feed-forward and feedback control technique is used to manipulate IP3 values to stabilise the concentration of Ca2+ inside the astrocytes. The theoretical analysis of the given model aims i) to stabilize the Ca2+ concentration around a particular desired level in order to prevent abnormal gliotransmitters' concentration (extremely high or low concentration can result in neurodegeneration), ii) to improve the molecular communication performance that utilises Ca2+ signalling, and maintain gliotransmitters' regulation remotely. It shows that the refractory periods from Ca2+ can be maintained to lower the noise propagation resulting in smaller time-slots for bit transmission, which can also improve the delay and gain performances. The proposed approach can potentially lead to novel nanomedicine solutions for the treatment of neurodegenerative diseases, where a combination of nanotechnology and gene therapy approaches can be used to elicit the regulated Ca2+ signalling in astrocytes, ultimately improving neuronal activity.

  • 19.
    Bartoszek, Krzysztof
    Gdansk University of Technology.
    A Graph – String Model of Gene Assembly in Ciliates2006Inngår i: Zeszyty Naukowe Wydzialu ETI Politechniki Gdanskiej, 2006, Vol. 10, s. 521-534Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The ciliates are a family of unicellular organisms that characterize themselves by having two types of nuclei, micro - and macronuclei. During cell mating the genetic material must change from the micronuclei to the macronuclei form. The paper summarises a formal model for this change. The model, which is described in recent works, is based on strings and graphs. It shows that inside the cell complex computational operations have to take place.

  • 20.
    Bartoszek, Krzysztof
    Gdansk University of Technology.
    The Bootstrap and Other Methods of Testing Phylogenetic Trees2007Inngår i: Zeszyty Naukowe Wydzialu ETI Politechniki Gdanskiej, 2007, Vol. 12, s. 103-108Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The final step of a phylogenetic analysis is the test of the generated tree. This is not a easy task for which there is an obvious methodology because we do not know the full probabilistic model of evolution. A number of methods have been proposed but there is a wide debate concerning the interpretations of the results they produce.

  • 21.
    Bartoszek, Krzysztof
    et al.
    Mathematical Sciences, Chalmers University of Technology and the University of Gothenburg.
    Liò, Pietro
    University of Cambridge.
    Sorathiya, Anil
    University of Cambridge.
    Influenza differentiation and evolution2010Inngår i: Acta Physica Polonica B Proceedings Supplement, 2010, Vol. 3, s. 417-452Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The aim of the study is to do a very wide analysis of HA, NA and M influenza gene segments to find short nucleotide regions,which differentiate between strains (i.e. H1, H2, ... e.t.c.), hosts, geographic regions, time when sequence was found and combination of time and region using a simple methodology. Finding regions  differentiating between strains has as its goal the construction of a Luminex microarray which will allow quick and efficient strain recognition. Discovery for the other splitting factors could shed lighton structures significant for host specificity and on the history of influenza evolution. A large number of places in the HA, NA and M gene segments were found that can differentiate between hosts, regions, time and combination of time and region. Also very good differentiation between different Hx strains can be seen.We link one of our findings to a proposed stochastic model of creation of viral phylogenetic trees.

  • 22.
    Bartoszek, Krzysztof
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen, Tillämpad matematik och statistik.
    Pietro, Lio'
    Cambridge University.
    A novel algorithm to reconstruct phylogenies using gene sequences and expression data2014Inngår i: International Proceedings of Chemical, Biological & Environmental Engineering; Environment, Energy and Biotechnology III, 2014, s. 8-12Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Phylogenies based on single loci should be viewed with caution and the best approach for obtaining robust trees is to examine numerous loci across the genome. It often happens that for the same set of species trees derived from different genes are in conflict between each other. There are several methods that combine information from different genes in order to infer the species tree. One novel approach is to use informationfrom different -omics. Here we describe a phylogenetic method based on an Ornstein–Uhlenbeck process that combines sequence and gene expression data. We test our method on genes belonging to the histidine biosynthetic operon. We found that the method provides interesting insights into selection pressures and adaptive hypotheses concerning gene expression levels.

  • 23.
    Bashardanesh, Zahedeh
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräkningsbiologi och bioinformatik.
    Lötstedt, Per
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions2018Inngår i: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 357, s. 78-99Artikkel i tidsskrift (Fagfellevurdert)
  • 24.
    Bebris, Kristaps
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för ekologi och genetik, Zooekologi. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för biologisk grundutbildning.
    Local adaptation of Grauer's gorilla gut microbiome2017Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    The availability of high-throughput sequencing technologies has enabled metagenomicinvestigations into complex bacterial communities with unprecedented resolution andthroughput. The production of dedicated data sets for metagenomic analyses is, however, acostly process and, frequently, the first research questions focus on the study species itself. Ifthe source material is represented by fecal samples, target capture of host-specific sequencesis applied to enrich the complex DNA mixtures contained within a typical fecal DNA extract.Yet, even after this enrichment, the samples still contain a large amount of environmentalDNA that is usually left unanalysed. In my study I investigate the possibility of using shotgunsequencing data that has been subjected to target enrichment for mtDNA from the hostspecies, Grauer’s gorilla (Gorilla beringei graueri), for further analysis of the microbialcommunity present in these samples. The purpose of these analyses is to study the differencesin the bacterial communities present within a high-altitude Grauer’s gorilla, low-altitudeGrauer’s gorilla, and a sympatric chimpanzee population. Additionally, I explore the adaptivepotential of the gut microbiota within these great ape populations.I evaluated the impact that the enrichment process had on the microbial community by usingpre- and post-capture museum preserved samples. In addition to this, I also analysed the effectof two different extraction methods on the bacterial communities.My results show that the relative abundances of the bacterial taxa remain relatively unaffectedby the enrichment process and the extraction methods. The overall number of taxa is,however, reduced by each additional capture round and is not consistent between theextraction methods. This means that both the enrichment and extraction processes introducebiases that require the usage of abundance-based distance measures for biological inferences.Additionally, even if the data cannot be used to study the bacterial communities in anunbiased manner, it provides useful comparative insights for samples that were treated in thesame fashion.With this background, I used museum and fecal samples to perform cluster analysis to explorethe relationships between the gut microbiota of the three great ape populations. I found thatpopulations cluster by species first, and only then group according to habitat. I further foundthat a bacterial taxon that degrades plant matter is enriched in the gut microbiota of all threegreat ape species, where it could help with the digestion of vegetative foods. Another bacterialtaxon that consumes glucose is enriched in the gut microbiota of the low-altitude gorilla andchimpanzee populations, where it could help with the modulation of the host’s mucosalimmune system, and could point to the availability of fruit in the animals diet. In addition, Ifound a bacterial taxon that is linked with diarrhea in humans to be part of the gut microbiotaof the habituated high-altitude gorilla population, which could indicate that this pathogen hasbeen transmitted to the gorillas from their interaction with humans, or it could be indicative ofthe presence of a contaminated water source.

  • 25.
    Bergman, Ebba
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Molekylär evolution.
    Haplotype Inference as a caseof Maximum Satisfiability: A strategy for identifying multi-individualinversion points in computational phasing2017Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    Phasing genotypes from sequence data is an important step betweendata gathering and downstream analysis in population genetics,disease studies, and multiple other fields. This determination ofthe sequences of markers corresponding to the individualchromosomes can be done on data where the markers are in lowdensity across the chromosome, such as from single nucleotidepolymorphism (SNP) microarrays, or on data with a higher localdensity of markers like in next generation sequencing (NGS). Thesorted markers may then be used for many different analyses anddata processing such as linkage analysis, or inference of missinggenotypes in the process of imputation

    cnF2freq is a haplotype phasing program that uses an uncommonapproach allowing it to divide big groups of related individualsinto smaller ones. It sets an initial haplotype phase and theniteratively changes it using estimations from Hidden MarkovModels. If a marker is judged to have been placed in the wronghaplotype, a switch needs to be made so that it belongs to thecorrect phase. The objective of this project was to go fromallowing only one individual within a group to be switched in aniteration to allowing multiple switches that are dependent on eachother.

    The result of this project is a theoretical solution for allowingmultiple dependent switches in cnF2freq, and an implementedsolution using the max-SAT solver toulbar2.

  • 26.
    Bornelöv, Susanne
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi.
    Rule-based Models of Transcriptional Regulation and Complex Diseases: Applications and Development2014Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    As we gain increased understanding of genetic disorders and gene regulation more focus has turned towards complex interactions. Combinations of genes or gene and environmental factors have been suggested to explain the missing heritability behind complex diseases. Furthermore, gene activation and splicing seem to be governed by a complex machinery of histone modification (HM), transcription factor (TF), and DNA sequence signals. This thesis aimed to apply and develop multivariate machine learning methods for use on such biological problems. Monte Carlo feature selection was combined with rule-based classification to identify interactions between HMs and to study the interplay of factors with importance for asthma and allergy.

    Firstly, publicly available ChIP-seq data (Paper I) for 38 HMs was studied. We trained a classifier for predicting exon inclusion levels based on the HMs signals. We identified HMs important for splicing and illustrated that splicing could be predicted from the HM patterns. Next, we applied a similar methodology on data from two large birth cohorts describing asthma and allergy in children (Paper II). We identified genetic and environmental factors with importance for allergic diseases which confirmed earlier results and found candidate gene-gene and gene-environment interactions.

    In order to interpret and present the classifiers we developed Ciruvis, a web-based tool for network visualization of classification rules (Paper III). We applied Ciruvis on classifiers trained on both simulated and real data and compared our tool to another methodology for interaction detection using classification. Finally, we continued the earlier study on epigenetics by analyzing HM and TF signals in genes with or without evidence of bidirectional transcription (Paper IV). We identified several HMs and TFs with different signals between unidirectional and bidirectional genes. Among these, the CTCF TF was shown to have a well-positioned peak 60-80 bp upstream of the transcription start site in unidirectional genes.

    Delarbeid
    1. Combinations of histone modifications mark exon inclusion levels
    Åpne denne publikasjonen i ny fane eller vindu >>Combinations of histone modifications mark exon inclusion levels
    2012 (engelsk)Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, nr 1, artikkel-id e29911Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Splicing is a complex process regulated by sequence at the classical splice sites and other motifs in exons and introns with an enhancing or silencing effect. In addition, specific histone modifications on nucleosomes positioned over the exons have been shown to correlate both positively and negatively with exon expression. Here, we trained a model of "IF … THEN …" rules to predict exon inclusion levels in a transcript from histone modification patterns. Furthermore, we showed that combinations of histone modifications, in particular those residing on nucleosomes preceding or succeeding the exon, are better predictors of exon inclusion levels than single modifications. The resulting model was evaluated with cross validation and had an average accuracy of 72% for 27% of the exons, which demonstrates that epigenetic signals substantially mark alternative splicing.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-175875 (URN)10.1371/journal.pone.0029911 (DOI)000312662100045 ()22242188 (PubMedID)
    Forskningsfinansiär
    Knut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research Swedish Research CouncilSwedish Cancer Society
    Tilgjengelig fra: 2012-06-13 Laget: 2012-06-13 Sist oppdatert: 2018-01-12bibliografisk kontrollert
    2. Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy
    Åpne denne publikasjonen i ny fane eller vindu >>Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy
    Vise andre…
    2013 (engelsk)Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, nr 11, s. e80080-Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children) and BAMSE (a Swedish birth-cohort including 2033 children), genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6) and 3.2 (95% CI 2.0-5.0) in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0) of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies of etiological mechanisms and may also strengthen the basis for risk assessment and prevention.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-213817 (URN)10.1371/journal.pone.0080080 (DOI)000327311900057 ()
    Tilgjengelig fra: 2014-01-05 Laget: 2014-01-04 Sist oppdatert: 2017-12-06bibliografisk kontrollert
    3. Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers
    Åpne denne publikasjonen i ny fane eller vindu >>Ciruvis: a web-based tool for rule networks and interaction detection using rule-based classifiers
    2014 (engelsk)Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 15, s. 139-Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Background: The use of classification algorithms is becoming increasingly important for the field of computational biology. However, not only the quality of the classification, but also its biological interpretation is important. This interpretation may be eased if interacting elements can be identified and visualized, something that requires appropriate tools and methods. Results: We developed a new approach to detecting interactions in complex systems based on classification. Using rule-based classifiers, we previously proposed a rule network visualization strategy that may be applied as a heuristic for finding interactions. We now complement this work with Ciruvis, a web-based tool for the construction of rule networks from classifiers made of IF-THEN rules. Simulated and biological data served as an illustration of how the tool may be used to visualize and interpret classifiers. Furthermore, we used the rule networks to identify feature interactions, compared them to alternative methods, and computationally validated the findings. Conclusions: Rule networks enable a fast method for model visualization and provide an exploratory heuristic to interaction detection. The tool is made freely available on the web and may thus be used to aid and improve rule-based classification.

    Emneord
    Visualization, Rules, Interactions, Interaction detection, Classification, Rule-based classification
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-228027 (URN)10.1186/1471-2105-15-139 (DOI)000336679600001 ()
    Tilgjengelig fra: 2014-07-02 Laget: 2014-07-02 Sist oppdatert: 2017-12-05bibliografisk kontrollert
    4. Different distribution of histone modifications in genes with unidirectional and bidirectional transcription and a role of CTCF and cohesin in directing transcription
    Åpne denne publikasjonen i ny fane eller vindu >>Different distribution of histone modifications in genes with unidirectional and bidirectional transcription and a role of CTCF and cohesin in directing transcription
    2015 (engelsk)Inngår i: BMC Genomics, ISSN 1471-2164, E-ISSN 1471-2164, Vol. 16, artikkel-id 300Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Background: Several post-translational histone modifications are mainly found in gene promoters and are associated with the promoter activity. It has been hypothesized that histone modifications regulate the transcription, as opposed to the traditional view with transcription factors as the key regulators. Promoters of most active genes do not only initiate transcription of the coding sequence, but also a substantial amount of transcription of the antisense strand upstream of the transcription start site (TSS). This promoter feature has generally not been considered in previous studies of histone modifications and transcription factor binding.

    Results: We annotated protein-coding genes as bi- or unidirectional depending on their mode of transcription and compared histone modifications and transcription factor occurrences between them. We found that H3K4me3, H3K9ac, and H3K27ac were significantly more enriched upstream of the TSS in bidirectional genes compared with the unidirectional ones. In contrast, the downstream histone modification signals were similar, suggesting that the upstream histone modifications might be a consequence of transcription rather than a cause. Notably, we found well-positioned CTCF and RAD21 peaks approximately 60-80 bp upstream of the TSS in the unidirectional genes. The peak heights were related to the amount of antisense transcription and we hypothesized that CTCF and cohesin act as a barrier against antisense transcription.

    Conclusions: Our results provide insights into the distribution of histone modifications at promoters and suggest a novel role of CTCF and cohesin as regulators of transcriptional direction.

    Emneord
    Antisense transcription, CTCF, RAD21, Cohesin, CAGE, Epigenetics, Transcription factor, Histone modification
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-230158 (URN)10.1186/s12864-015-1485-5 (DOI)000355166000001 ()25881024 (PubMedID)
    Tilgjengelig fra: 2014-08-19 Laget: 2014-08-19 Sist oppdatert: 2017-12-05bibliografisk kontrollert
  • 27.
    Bornelöv, Susanne
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Enroth, Stefan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Genomik. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Komorowski, Jan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Visualization of Rules in Rule-Based Classifiers2012Inngår i: INTELLIGENT DECISION TECHNOLOGIES (IDT'2012), VOL 1, 2012, Vol. 15, s. 329-338Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Interpretation and visualization of the classification models are important parts of machine learning. Rule-based classifiers often contain too many rules to be easily interpreted by humans, and methods for post-classification analysis of the rules are needed. Here we present a strategy for circular visualization of sets of classification rules. The Circos software was used to generate graphs showing all pairs of conditions that were present in the rules as edges inside a circle. We showed using simulated data that all two-way interactions in the data were found by the classifier and displayed in the graph, although the single attributes were constructed to have no correlation to the decision class. For all examples we used rules trained using the rough set theory, but the visualization would by applicable to any sort of classification rules. This method for rule visualization may be useful for applications where interaction terms are expected, and the size of the model limits the interpretability.

  • 28.
    Bouchnita, Anass
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Volpert, Vitaly
    A multiscale model of platelet-fibrin thrombus growth in the flow2019Inngår i: Computers & Fluids, ISSN 0045-7930, E-ISSN 1879-0747Artikkel i tidsskrift (Fagfellevurdert)
  • 29.
    Boukharta, Lars
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi.
    Gutierréz de Terán, Hugo
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi.
    Åqvist, Johan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi.
    Computational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptors2014Inngår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 10, nr 4, s. e1003585-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Site-directed mutagenesis combined with binding affinity measurements is widely used to probe the nature of ligand interactions with GPCRs. Such experiments, as well as structure-activity relationships for series of ligands, are usually interpreted with computationally derived models of ligand binding modes. However, systematic approaches for accurate calculations of the corresponding binding free energies are still lacking. Here, we report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 receptor and series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Author Summary G-protein coupled receptors constitute a family of drug targets of outstanding interest, with more than 30% of the marketed drugs targeting a GPCR. The combination of site-directed mutagenesis, biochemical experiments and computationally generated 3D structural models has traditionally been used to investigate these receptors. The increasing number of GPCR crystal structures now paves the way for detailed characterization of receptor-ligand interactions and energetics using advanced computer simulations. Here, we present an accurate computational scheme to predict and interpret the effects of alanine scanning experiments, based on molecular dynamics free energy simulations. We apply the technique to antagonist binding to the neuropeptide Y receptor Y1, the structure of which is still unknown. A structural model of a Y1-antagonist complex was derived and used as starting point for computational characterization of the effects on binding of alanine substitutions at thirteen different receptor positions. Further, we used the model and computational scheme to predict the binding of a series of seven antagonist analogs. The results are in excellent agreement with available experimental data and provide validation of both the methodology and structural models of the complexes.

  • 30.
    Bringeland, Nathalie
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för neurovetenskap, Funktionell farmakologi. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för biologisk grundutbildning.
    DNA methylation correlation networks in overweight and normal-weight adolescents reveal differential coordination2013Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Multiple health issues are associated with obesity and numerous factors are causative of the disease. The role of genetic factors is well established, as is the knowledge that dietary and sedentary behavior promotes weight gain. Although there is strong suspicion towards the role of epigenetics as a driving force toward disease, this field remains l in the context of obesity. DNA methylation correlation networks were profiled from blood samples of 69 adolescents of two distinct weight-classes; obese (n=35) and normal-weight (n=34). The network analysis revealed major differences in the organization of the networks where the network of the obese had less modularity compared to normal-weight. This is manifested by more and smaller clusters in the obese, pertaining to genes of related functions and pathways, than the network of the normal-weight. Consequently, this suggests that biological pathways have a lower order of coordination between each other in means of DNA methylation in obese than normal-weight. Analysis of highly connected genes, hubs, in the two networks suggests that the difference in coordination between biological pathways may be derived by changes of the methylation pattern of these hubs; highly connected genes in one network had an intriguingly low connectivity in the other. In conclusion, the results suggest differential regulation of transcription through changes in the coordination of DNA methylation in overweight and normal weighted individuals. The findings of this study are a major step towards understanding the role of DNA methylation in obesity and provide potential biomarkers for diagnosing and predicting obesity.

  • 31.
    Bäcklin, Christofer
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Machine Learning Based Analysis of DNA Methylation Patterns in Pediatric Acute Leukemia2015Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer in the Nordic countries. Recent evidence indicate that DNA methylation (DNAm) play a central role in the development and progression of the disease.

    DNAm profiles of a collection of ALL patient samples and a panel of non-leukemic reference samples were analyzed using the Infinium 450k methylation assay. State-of-the-art machine learning algorithms were used to search the large amounts of data produced for patterns predictive of future relapses, in vitro drug resistance, and cytogenetic subtypes, aiming at improving our understanding of the disease and ultimately improving treatment.

    In paper I, the predictive modeling framework developed to perform the analyses of DNAm dataset was presented. It focused on uncompromising statistical rigor and computational efficiency, while allowing a high level of modeling flexibility and usability. In paper II, the DNAm landscape of ALL was comprehensively characterized, discovering widespread aberrant methylation at diagnosis strongly influenced by cytogenetic subtype. The aberrantly methylated regions were enriched for genes repressed by polycomb group proteins, repressively marked histones in healthy cells, and genes associated with embryonic development. A consistent trend of hypermethylation at relapse was also discovered. In paper III, a tool for DNAm-based subtyping was presented, validated using blinded samples and used to re-classify samples with incomplete phenotypic information. Using RNA-sequencing, previously undetected non-canonical aberrations were found in many re-classified samples. In paper IV, the relationship between DNAm and in vitro drug resistance was investigated and predictive signatures were obtained for seven of the eight therapeutic drugs studied. Interpretation was challenging due to poor correlation between DNAm and gene expression, further complicated by the discovery that random subsets of the array can yield comparable classification accuracy. Paper V presents a novel Bayesian method for multivariate density estimation with variable bandwidths. Simulations showed comparable performance to the current state-of-the-art methods and an advantage on skewed distributions.

    In conclusion, the studies characterize the information contained in the aberrant DNAm patterns of ALL and assess its predictive capabilities for future relapses, in vitro drug sensitivity and subtyping. They also present three publicly available tools for the scientific community to use.

    Delarbeid
    1. Developer-Friendly and Computationally Efficient Predictive Modeling without Information Leakage: The emil Package for R
    Åpne denne publikasjonen i ny fane eller vindu >>Developer-Friendly and Computationally Efficient Predictive Modeling without Information Leakage: The emil Package for R
    2018 (engelsk)Inngår i: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 85, nr 13, s. 1-30Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Data driven machine learning for predictive modeling problems (classification, regression, or survival analysis) typically involves a number of steps beginning with data preprocessing and ending with performance evaluation. A large number of packages providing tools for the individual steps are available for R, but there is a lack of tools for facilitating rigorous performance evaluation of the complete procedures assembled from them by means of cross-validation, bootstrap, or similar methods. Such a tool should strictly prevent test set observations from influencing model training and meta- parameter tuning, so- called information leakage, in order to not produce overly optimistic performance estimates. Here we present a new package for R denoted emil (evaluation of modeling without information leakage) that offers this form of performance evaluation. It provides a transparent and highly customizable framework for facilitating the assembly, execution, performance evaluation, and interpretation of complete procedures for classification, regression, and survival analysis. The components of package emil have been designed to be as modular and general as possible to allow users to combine, replace, and extend them if needed. Package emil was also developed with scalability in mind and has a small computational overhead, which is a key requirement for analyzing the very big data sets now available in fields like medicine, physics, and finance. First package emil's functionality and usage is explained. Then three specific application examples are presented to show its potential in terms of parallelization, customization for survival analysis, and development of ensemble models. Finally a brief comparison to similar software is provided.

    sted, utgiver, år, opplag, sider
    JOURNAL STATISTICAL SOFTWARE, 2018
    Emneord
    predictive modeling, machine learning, performance evaluation, resampling, high performance computing
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-362159 (URN)10.18637/jss.v085.i13 (DOI)000440230100001 ()
    Forskningsfinansiär
    Swedish Foundation for Strategic Research , RBc08-008Swedish Research Council, 621-2008-5854
    Tilgjengelig fra: 2018-10-19 Laget: 2018-10-19 Sist oppdatert: 2018-10-19bibliografisk kontrollert
    2. Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia
    Åpne denne publikasjonen i ny fane eller vindu >>Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia
    Vise andre…
    2013 (engelsk)Inngår i: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 14, nr 9, s. r105-Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    BACKGROUND:

    Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood.

    RESULTS:

    We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status.

    CONCLUSIONS:

    Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-208296 (URN)10.1186/gb-2013-14-9-r105 (DOI)000328195700011 ()24063430 (PubMedID)
    Merknad

    De två första författarna delar förstaförfattarskapet.

    Tilgjengelig fra: 2013-09-27 Laget: 2013-09-27 Sist oppdatert: 2018-01-11bibliografisk kontrollert
    3. DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
    Åpne denne publikasjonen i ny fane eller vindu >>DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
    Vise andre…
    2015 (engelsk)Inngår i: Clinical Epigenetics, E-ISSN 1868-7083, Vol. 7, artikkel-id 11Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Background

    We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL.

    Results

    We used the methylation status of ~450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations (‘other’ subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5.

    Conclusions

    Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-242351 (URN)10.1186/s13148-014-0039-z (DOI)000350260800001 ()25729447 (PubMedID)
    Forskningsfinansiär
    Swedish Foundation for Strategic Research , RBc08-008
    Merknad

    De två sista författarna delar sistaförfattarskapet.

    Tilgjengelig fra: 2015-01-25 Laget: 2015-01-25 Sist oppdatert: 2017-12-05bibliografisk kontrollert
    4. DNA methylation-based prediction of in vitro drug resistance in primary pediatric acute lymphoblastic leukemia patient samples
    Åpne denne publikasjonen i ny fane eller vindu >>DNA methylation-based prediction of in vitro drug resistance in primary pediatric acute lymphoblastic leukemia patient samples
    Vise andre…
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-242543 (URN)
    Forskningsfinansiär
    Swedish Foundation for Strategic Research , RBc08-008
    Tilgjengelig fra: 2015-01-27 Laget: 2015-01-27 Sist oppdatert: 2018-01-11
    5. Bayesian model averaging of adaptive bandwidth kernel density estimators yields state-of-the-art performance
    Åpne denne publikasjonen i ny fane eller vindu >>Bayesian model averaging of adaptive bandwidth kernel density estimators yields state-of-the-art performance
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    Emneord
    Variable kernel density estimation, adaptive kernel density estimation, Bayesian model averaging, variable bandwidth, square root law
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-242354 (URN)
    Forskningsfinansiär
    Swedish Foundation for Strategic Research , RBc08-008EU, FP7, Seventh Framework Programme, PROACTIVE
    Tilgjengelig fra: 2015-01-27 Laget: 2015-01-25 Sist oppdatert: 2015-03-11
  • 32.
    Bäcklin, Christofer
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Freyhult, Eva
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Frost, Britt-Marie
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Pediatrik.
    Palle, Josefine
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Pediatrik.
    Larsson, Rolf
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    Syvänen, Ann-Christine
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin.
    Lönnerholm, Gudmar
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kvinnors och barns hälsa, Pediatrik.
    Gustafsson, Mats
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
    DNA methylation-based prediction of in vitro drug resistance in primary pediatric acute lymphoblastic leukemia patient samplesManuskript (preprint) (Annet vitenskapelig)
  • 33.
    Capuccini, Marco
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för biologisk grundutbildning.
    Structure-Based Virtual Screening in Spark2015Independent thesis Advanced level (degree of Master (Two Years)), 30 poäng / 45 hpOppgave
  • 34.
    Capuccini, Marco
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Ahmed, Laeeq
    Schaal, Wesley
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Laure, Erwin
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Large-scale virtual screening on public cloud resources with Apache Spark2017Inngår i: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 9, artikkel-id 15Artikkel i tidsskrift (Fagfellevurdert)
  • 35.
    Carreras-Puigvert, Jordi
    et al.
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Zitnik, Marinka
    Univ Ljubljana, Fac Comp & Informat Sci, SI-1000 Ljubljana, Slovenia.; Stanford Univ, Dept Comp Sci, Palo Alto, CA 94305 USA.
    Jemth, Ann-Sofie
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Carter, Megan
    Stockholm Univ, Dept Biochem & Biophys, S-10691 Stockholm, Sweden.
    Unterlass, Judith E
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Hallström, Björn
    KTH Royal Inst Technol, Sci Life Lab, Cell Profiling Affin Prote, S-17165 Stockholm, Sweden.
    Loseva, Olga
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Karem, Zhir
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Calderón-Montaño, José Manuel
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    Lindskog, Cecilia
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Edqvist, Per-Henrik D
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Experimentell och klinisk onkologi.
    Matuszewski, Damian J.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Ait Blal, Hammou
    KTH Royal Inst Technol, Sci Life Lab, Cell Profiling Affin Prote, S-17165 Stockholm, Sweden.
    Berntsson, Ronnie P A
    Stockholm Univ, Dept Biochem & Biophys, S-10691 Stockholm, Sweden.
    Häggblad, Maria
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Biochem & Cellular Screening Facil, S-17165 Stockholm, Sweden.
    Martens, Ulf
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Biochem & Cellular Screening Facil, S-17165 Stockholm, Sweden.
    Studham, Matthew
    Stockholm Univ, Dept Biochem & Biophys, Stockholm Bioinformat Ctr, Sci Life Lab, Box 1031, S-17121 Solna, Sweden.
    Lundgren, Bo
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Biochem & Cellular Screening Facil, S-17165 Stockholm, Sweden.
    Wählby, Carolina
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sonnhammer, Erik L L
    Stockholm Univ, Dept Biochem & Biophys, Stockholm Bioinformat Ctr, Sci Life Lab, Box 1031, S-17121 Solna, Sweden.
    Lundberg, Emma
    KTH Royal Inst Technol, Sci Life Lab, Cell Profiling Affin Prote, S-17165 Stockholm, Sweden.
    Stenmark, Pål
    Stockholm Univ, Dept Biochem & Biophys, S-10691 Stockholm, Sweden.
    Zupan, Blaz
    Univ Ljubljana, Fac Comp & Informat Sci, SI-1000 Ljubljana, Slovenia.; Baylor Coll Med, Dept Mol & Human Genet, Houston, TX 77030 USA.
    Helleday, Thomas
    Karolinska Inst, Div Translat Med & Chem Biol, Dept Mol Biochem & Biophys, Sci Life Lab, S-17165 Stockholm, Sweden.
    A comprehensive structural, biochemical and biological profiling of the human NUDIX hydrolase family2017Inngår i: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, nr 1, artikkel-id 1541Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The NUDIX enzymes are involved in cellular metabolism and homeostasis, as well as mRNA processing. Although highly conserved throughout all organisms, their biological roles and biochemical redundancies remain largely unclear. To address this, we globally resolve their individual properties and inter-relationships. We purify 18 of the human NUDIX proteins and screen 52 substrates, providing a substrate redundancy map. Using crystal structures, we generate sequence alignment analyses revealing four major structural classes. To a certain extent, their substrate preference redundancies correlate with structural classes, thus linking structure and activity relationships. To elucidate interdependence among the NUDIX hydrolases, we pairwise deplete them generating an epistatic interaction map, evaluate cell cycle perturbations upon knockdown in normal and cancer cells, and analyse their protein and mRNA expression in normal and cancer tissues. Using a novel FUSION algorithm, we integrate all data creating a comprehensive NUDIX enzyme profile map, which will prove fundamental to understanding their biological functionality.

  • 36.
    Che, Huiwen
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för biologisk grundutbildning.
    Evaluation of de novo assembly using PacBio long reads2016Independent thesis Advanced level (degree of Master (One Year)), 10 poäng / 15 hpOppgave
    Abstract [en]

    New sequencing technologies show promise for the construction of complete and accurate genome sequences, by a process called de novo assembly that joins reads by overlap to longer contiguous sequences without the need for a reference genome. High-quality de novo assembly leads to better understanding in genetic variations. The purpose of this thesis is to evaluate human genome sequences obtained from the PacBio sequencing platform, which is a new technology suitable for de novo assembly of large genomes. The evaluation focuses on comparing sequence identity between our own de novo assemblies and the available human reference and through that, benchmark accuracy of our data. Sequences that are absent from the reference genome, are investigated for potential unannotated genes coordinately. We also assess the complex structural variation using different approaches. Our assemblies show high consensus with the human reference genome, with ⇠ 98.6% of the bases in the assemblies mapped to the human reference. We also detect more than ten thousand of structural variants, including some large rearrangements, with respect to the reference.

  • 37.
    Christoffersson, Gustaf
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
    Lomei, Jalal
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
    O'Callaghan, Paul
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
    Kreuger, Johan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
    Engblom, Stefan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Tillämpad beräkningsvetenskap.
    Phillipson, Mia
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk cellbiologi.
    Vascular sprouts induce local attraction of proangiogenic neutrophils2017Inngår i: Journal of Leukocyte Biology, ISSN 0741-5400, E-ISSN 1938-3673, Vol. 102, s. 741-751Artikkel i tidsskrift (Fagfellevurdert)
  • 38.
    Clauson, Björn
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap.
    Evaluation of methodologies for estimation of change in systemic drug exposure in renally impaired patients: Elucidation of possible causes to discrepancies in results based on phase I and III data2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Introduction: Regulatory authorities require certain subpopulations, such as patients with renal impairment (RI) to be studied specifically. This may be done in phase I analyzed with Non-Compartmental Analysis (NCA), and/or as part of phase III utilizing population pharmacokinetic (PopPK) methods. However, it has been suggested that phase I data analyzed with NCA may overestimate the effect of RI, as compared with PopPK analysis.

    Aim:  This project aimed to investigate causes for the discrepancy previously observed when calculating the exposure increase over different RI groups based on phase I and III data, and to examine the effect of erroneous assumptions made during PopPK model development, which can be of potential benefit in drug development.

    Materials and Methods: Phase I and III data were simulated based on PopPK models. Potential causes, related to the methods used, to the over-prediction by NCA were investigated. For phase III data the influence of model misspecification on the estimation of exposure increase in RI was explored.

    Results: The observed over-predictions by NCA were suggested to be due mainly to sub-optimal NCA and bias calculations, the latter with respect to creatinine clearance (CrCL) reference value. In PopPK analysis of phase III data, using erroneous structural and/or covariate model may result in severe bias in the estimation of the effect of RI, while disregarding the effect of inter-occasion variability led to low bias. 

    Conclusions: The previously observed over-prediction by the NCA method appears to mainly be an artefact due to inappropriate methodology. When investigating exposure increase in RI patients using PopPK for phase III data, careful consideration regarding assumptions should be made, especially with lower fraction excreted, as results suggest large bias when an erroneous PopPK model is applied. 

  • 39.
    Dahlberg, Johan
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin.
    Genetic Cartography at Massively Parallel Scale2018Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Massively parallel sequencing (MPS) is revolutionizing genomics. In this work we use, refine, and develop new tools for the discipline.

    MPS has led to the discovery of multiple novel subtypes in Acute Lymphoblastic Leukemia (ALL). In Study I we screen for fusion genes in 134 pediatric ALL patients, including patients without an assigned subtype. In approximately 80% of these patients we detect novel or known fusion gene families, most of which display distinct methylation and expression patterns. This shows the potential for improvements in the clinical stratification of ALL. Large sample sizes are important to detect recurrent somatic variation. In Study II we investigate if a non-index overlapping pooling schema can be used to increase sample size and detect somatic variation. We designed a schema for 172 ALL samples and show that it is possible to use this method to call somatic variants.

    Around the globe there are many ongoing and completed genome projects. In Study III we sequenced the genome of 1000 Swedes to create a reference data set for the Swedish population. We identified more than 10 million variants that were not present in publicly available databases, highlighting the need for population-specific resources. Data, and the tools developed during this study, have been made publicly available as a resource for genomics in Sweden and abroad.

    The increased amount of sequencing data has created a greater need for automation. In Study IV we present Arteria, a computational automation system for sequencing core facilities. This system has been adopted by multiple facilities and has been used to analyze thousands of samples. In Study V we developed CheckQC, a program that provides automated quality control of Illumina sequencing runs. These tools make scaling up MPS less labour intensive, a key to unlocking the full future potential of genomics.

    The tools, and data presented here are a valuable contribution to the scientific community. Collectively they showcase the power of MPS and genomics to bring about new knowledge of human health and disease.

    Delarbeid
    1. Transcriptome sequencing in pediatric acute lymphoblastic leukemia identifies fusion genes associated with distinct DNA methylation profiles
    Åpne denne publikasjonen i ny fane eller vindu >>Transcriptome sequencing in pediatric acute lymphoblastic leukemia identifies fusion genes associated with distinct DNA methylation profiles
    Vise andre…
    2017 (engelsk)Inngår i: Journal of Hematology & Oncology, ISSN 1756-8722, E-ISSN 1756-8722, Vol. 10, artikkel-id 148Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Background: Structural chromosomal rearrangements that lead to expressed fusion genes are a hallmark of acute lymphoblastic leukemia (ALL). In this study, we performed transcriptome sequencing of 134 primary ALL patient samples to comprehensively detect fusion transcripts. Methods: We combined fusion gene detection with genome-wide DNA methylation analysis, gene expression profiling, and targeted sequencing to determine molecular signatures of emerging ALL subtypes. Results: We identified 64 unique fusion events distributed among 80 individual patients, of which over 50% have not previously been reported in ALL. Although the majority of the fusion genes were found only in a single patient, we identified several recurrent fusion gene families defined by promiscuous fusion gene partners, such as ETV6, RUNX1, PAX5, and ZNF384, or recurrent fusion genes, such as DUX4-IGH. Our data show that patients harboring these fusion genes displayed characteristic genome-wide DNA methylation and gene expression signatures in addition to distinct patterns in single nucleotide variants and recurrent copy number alterations. Conclusion: Our study delineates the fusion gene landscape in pediatric ALL, including both known and novel fusion genes, and highlights fusion gene families with shared molecular etiologies, which may provide additional information for prognosis and therapeutic options in the future.

    Emneord
    Pediatric acute lymphoblastic leukemia, RNA sequencing, Fusion genes, BCP-ALL, T-ALL, Translocation
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-332658 (URN)10.1186/s13045-017-0515-y (DOI)000408001300001 ()28806978 (PubMedID)
    Forskningsfinansiär
    Swedish Foundation for Strategic Research , RBc08-008Swedish Cancer Society, 130440, 160711Swedish Childhood Cancer Foundation, 11098Swedish Research Council, C0524801, 2016-03691_3
    Merknad

    De 2 sista författarna delar sistaförfattarskapet.

    Tilgjengelig fra: 2017-10-31 Laget: 2017-10-31 Sist oppdatert: 2018-08-27bibliografisk kontrollert
    2. Identification of somatic variants by targeted sequencing of pooled cancer samples
    Åpne denne publikasjonen i ny fane eller vindu >>Identification of somatic variants by targeted sequencing of pooled cancer samples
    Vise andre…
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Forskningsprogram
    Medicinsk genetik
    Identifikatorer
    urn:nbn:se:uu:diva-269752 (URN)
    Tilgjengelig fra: 2015-12-18 Laget: 2015-12-18 Sist oppdatert: 2018-08-27
    3. SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population
    Åpne denne publikasjonen i ny fane eller vindu >>SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population
    Vise andre…
    2017 (engelsk)Inngår i: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 25, nr 11, s. 1253-1260Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

    sted, utgiver, år, opplag, sider
    NATURE PUBLISHING GROUP, 2017
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-337314 (URN)10.1038/ejhg.2017.130 (DOI)000412823800012 ()28832569 (PubMedID)
    Forskningsfinansiär
    Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceKnut and Alice Wallenberg Foundation, 2014.0272Swedish Research CouncilSwedish National Infrastructure for Computing (SNIC), sens2016003EU, European Research Council, 282330
    Tilgjengelig fra: 2018-01-08 Laget: 2018-01-08 Sist oppdatert: 2018-08-27bibliografisk kontrollert
    4. Arteria: An automation system for a sequencing core facility
    Åpne denne publikasjonen i ny fane eller vindu >>Arteria: An automation system for a sequencing core facility
    Vise andre…
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-357972 (URN)
    Tilgjengelig fra: 2018-08-23 Laget: 2018-08-23 Sist oppdatert: 2018-08-27
    5. CheckQC: Quick quality control of Illumina sequencing runs
    Åpne denne publikasjonen i ny fane eller vindu >>CheckQC: Quick quality control of Illumina sequencing runs
    2018 (engelsk)Inngår i: The Journal of Open Source Software, ISSN 2475-9066, Vol. 3, nr 22, artikkel-id 556Artikkel i tidsskrift (Fagfellevurdert) Published
    Emneord
    bioinformatics, sequencing
    HSV kategori
    Forskningsprogram
    Bioinformatik
    Identifikatorer
    urn:nbn:se:uu:diva-349255 (URN)10.21105/joss.00556 (DOI)
    Tilgjengelig fra: 2018-04-24 Laget: 2018-04-24 Sist oppdatert: 2018-08-27bibliografisk kontrollert
  • 40.
    Dahlberg, Johan
    et al.
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Hermansson, Johan
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin.
    Sturlaugsson, Steinar
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Smeds, Patrik
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi.
    Ladenvall, Claes
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi.
    Valls Guimera, Roman
    University of Melbourne Center for Cancer Research, University of Melbourne, Melbourne, Australia.
    Reisinger, Florian
    University of Melbourne Center for Cancer Research, University of Melbourne, Melbourne, Australia.
    Hofmann, Oliver
    University of Melbourne Center for Cancer Research, University of Melbourne, Melbourne, Australia.
    Larsson, Pontus
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Molekylär medicin. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Arteria: An automation system for a sequencing core facilityManuskript (preprint) (Annet vitenskapelig)
  • 41.
    Dahlqvist, Bengt
    et al.
    Uppsala universitet.
    Bengtsson, Ewert
    Uppsala universitet.
    Eriksson, Olle
    Uppsala universitet.
    Jarkrans, Torsten
    Uppsala universitet.
    Nordin, Bo
    Uppsala universitet.
    Stenkvist, Björn
    A Computer Program for Logistic Prediction Modelling1985Inngår i: Computer Programs in Biomedicine, ISSN 0010-468X, nr 19, s. 235-238Artikkel i tidsskrift (Fagfellevurdert)
  • 42.
    Dahlö, Martin
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Haziza, Frédéric
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi.
    Kallio, Aleksi
    Korpelainen, Eija
    Bongcam-Rudloff, Erik
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    BioImg.org: A catalog of virtual machine images for the life sciences2015Inngår i: Bioinformatics and Biology Insights, ISSN 1177-9322, E-ISSN 1177-9322, Vol. 9, s. 125-128Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education.

  • 43.
    Dahlö, Martin
    et al.
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi.
    Scofield, Douglas
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för ekologi och genetik, Evolutionsbiologi.
    Schaal, Wesley
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Spjuth, Ola
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för farmaceutisk biovetenskap. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Tracking the NGS revolution: managing life science research on shared high-performance computing clusters2018Inngår i: GigaScience, ISSN 2047-217X, E-ISSN 2047-217X, Vol. 7, nr 5, artikkel-id giy028Artikkel i tidsskrift (Fagfellevurdert)
  • 44.
    Dakshinamurthi, Ashwin Kumar
    et al.
    Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, India.
    Chidambaram, Manthira Vasagam
    Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, India.
    Manivel, Vivek Anand
    Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, India.
    Detchanamurthy, Swaminathan
    Department of Chemical and Process Engineering, University of Canterbury, Christchurch, New Zealand.
    Site directed mutagenesis of human Interleukin-2 gene to increase the stability of the gene product: A Bioinformatics Approach2009Inngår i: International Journal of Bioinformatics Research, ISSN 0975–3087, Vol. 1, nr 2, s. 4-13Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Interleukin-2 (IL-2) is an immunoregulatory cytokine whose biological effects are mediated through interaction with specific receptors on the surface of target cells. Due to its presumed role in generating a normal immune response, IL-2 is being evaluated for the treatment of a variety of tumors, in addition to infectious diseases. Main drawback of human IL-2 is that the molecule is relatively unstable. Therefore, with the objective of increasing the stability of the molecule, site directed mutagenesis of human IL-2 gene was carried out. Early studies indicated that mutations at three Cysteine residues (58, 105, 125) which are in the active sites of human IL-2 resulted in the reduced stability as well as the biological activity of the molecule. Therefore, mutations were carried out at the positions of amino acid other than the receptor binding sites at 111Valine to Arginine, 117Lysine to Glutamine and 133 Threonine to Asparagine of the human sequence by comparing it with the bovine sequence which has higher stability than the human counterpart, using SWISS PDB tool. To understand the biological activity of the mutated IL-2, energy minimization studies were carried out using SWISS-PDB. Docking studies were performed to check the reliability of the results using HEX DOCK, ARGUS LAB and PATCH DOCK between the IL-2 receptor and its mutated Ligand. These docking results also confirmed that the reliability of these mutated IL-2 gene. Stability, half life and ADME characteristics of these mutants can be studied in a detailed manner in the in vivo studies.

  • 45. Das, Sarbashis
    et al.
    Duggal, Priyanka
    Roy, Rahul
    Myneedu, Vithal P
    Behera, Digamber
    Prasad, Hanumanthappa K
    Bhattacharya, Alok
    Identification of hot and cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts.2012Inngår i: Scientific reports, ISSN 2045-2322, Vol. 2, s. 297-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The organization of genomic sequences is dynamic and undergoes change during the process of evolution. Many of the variations arise spontaneously and the observed genomic changes can either be distributed uniformly throughout the genome or be preferentially localized to some regions (hot spots) compared to others. Conversely cold spots may tend to accumulate very few variations or none at all. In order to identify such regions statistically, we have developed a method based on Shewhart Control Chart. The method was used for identification of hot and cold spots of single-nucleotide variations (SNVs) in Mycobacterium tuberculosis genomes. The predictions have been validated by sequencing some of these regions derived from clinical isolates. This method can be used for analysis of other genome sequences particularly infectious microbes.

  • 46. Das, Sarbashis
    et al.
    Roychowdhury, Tanmoy
    Kumar, Parameet
    Kumar, Anil
    Kalra, Priya
    Singh, Jitendra
    Singh, Sarman
    Prasad, H K
    Bhattacharya, Alok
    Genetic heterogeneity revealed by sequence analysis of Mycobacterium tuberculosis isolates from extra-pulmonary tuberculosis patients.2013Inngår i: BMC genomics, ISSN 1471-2164, Vol. 14, s. 404-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    BACKGROUND: Tuberculosis remains a major public health problem. Clinical tuberculosis manifests often as pulmonary and occasionally as extra-pulmonary tuberculosis. The emergence of drug resistant tubercle bacilli and its association with HIV is a formidable challenge to curb the spread of tuberculosis. There have been concerted efforts by whole genome sequencing and bioinformatics analysis to identify genomic patterns and to establish a relationship between the genotype of the organism and clinical manifestation of tuberculosis. Extra-pulmonary TB constitutes 15-20 percent of the total clinical cases of tuberculosis reported among immunocompetent patients, whereas among HIV patients the incidence is more than 50 percent. Genomic analysis of M. tuberculosis isolates from extra pulmonary patients has not been explored.

    RESULTS: The genomic DNA of 5 extra-pulmonary clinical isolates of M. tuberculosis derived from cerebrospinal fluid, lymph node fine needle aspirates (FNAC) / biopsies, were sequenced. Next generation sequencing approach (NGS) was employed to identify Single Nucleotide Variations (SNVs) and computational methods used to predict their consequence on functional genes. Analysis of distribution of SNVs led to the finding that there are mixed genotypes in patient isolates and that many SNVs are likely to influence either gene function or their expression. Phylogenetic relationship between the isolates correlated with the origin of the isolates. In addition, insertion sites of IS elements were identified and their distribution revealed a variation in number and position of the element in the 5 extra-pulmonary isolates compared to the reference M. tuberculosis H37Rv strain.

    CONCLUSIONS: The results suggest that NGS sequencing is able to identify small variations in genomes of M. tuberculosis isolates including changes in IS element insertion sites. Moreover, variations in isolates of M. tuberculosis from non-pulmonary sites were documented. The analysis of our results indicates genomic heterogeneity in the clinical isolates.

  • 47. Das, Sarbashis
    et al.
    Vishnoi, Anchal
    Bhattacharya, Alok
    ABWGAT: anchor-based whole genome analysis tool.2009Inngår i: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 25, nr 24, s. 3319-20Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    SUMMARY: Large numbers of genomes are being sequenced regularly and the rate will go up in future due to availability of new genome sequencing techniques. In order to understand genotype to phenotype relationships, it is necessary to identify sequence variations at the genomic level. Alignment of a pair of genomes and parsing the alignment data is an accepted approach for identification of variations. Though there are a number of tools available for whole-genome alignment, none of these allows automatic parsing of the alignment and identification of different kinds of genomic variants with high degree of sensitivity. Here we present a simple web-based interface for whole genome comparison named ABWGAT (Anchor-Based Whole Genome Analysis Tool) that is simple to use. The output is a list of variations such as SNVs, indels, repeat expansion and inversion.

    AVAILABILITY: The web server is freely available to non-commercial users at the following address http://abwgc.jnu.ac.in/_sarba. Supplementary data are available at http://abwgc.jnu.ac.in/_sarba/cgi-bin/abwgc_retrival.cgi using job id 524, 526 and 528.

    CONTACT: dsarbashis@gmail.com; alok.bhattacharya@gmail.com

  • 48.
    D'Elia, Domenica
    et al.
    Institute for Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy.
    Gisel, Andreas
    Institute for Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy.
    Eriksson, Nils-Einar
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Centrum för bioinformatik.
    Kossida, Sophia
    Bioinformatics & Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece.
    Mattila, Kimmo
    CSC – IT Center for Science Ltd., Keilaranta 14, 02100 Espoo, Finland.
    Klucar, Lubos
    Institute of Molecular Biology, Slovak Academy of Sciences, Dubravska cesta 21, 84551 Bratislava, Slovakia.
    Bongcam-Rudloff, Erik
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, 75024 Uppsala, Sweden.
    The 20th anniversary of EMBnet: 20 years of bioinformatics for the Life Sciences community2009Inngår i: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 10, nr Suppl. 6, s. S1-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The EMBnet Conference 2008, focusing on 'Leading Applications and Technologies in Bioinformatics', was organized by the European Molecular Biology network (EMBnet) to celebrate its 20th anniversary. Since its foundation in 1988, EMBnet has been working to promote collaborative development of bioinformatics services and tools to serve the European community of molecular biology laboratories. This conference was the first meeting organized by the network that was open to the international scientific community outside EMBnet. The conference covered a broad range of research topics in bioinformatics with a main focus on new achievements and trends in emerging technologies supporting genomics, transcriptomics and proteomics analyses such as high-throughput sequencing and data managing, text and data-mining, ontologies and Grid technologies. Papers selected for publication, in this supplement to BMC Bioinformatics, cover a broad range of the topics treated, providing also an overview of the main bioinformatics research fields that the EMBnet community is involved in.

  • 49.
    Dvirnas, Albertas
    et al.
    Lund Univ, Dept Astron & Theoret Phys, Lund, Sweden..
    Pichler, Christoffer
    Lund Univ, Dept Astron & Theoret Phys, Lund, Sweden..
    Stewart, Callum L.
    Lund Univ, Dept Astron & Theoret Phys, Lund, Sweden..
    Quaderi, Saair
    Lund Univ, Dept Astron & Theoret Phys, Lund, Sweden.;Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Nyberg, Lena K.
    Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Muller, Vilhelm
    Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Bikkarolla, Santosh Kumar
    Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Kristiansson, Erik
    Univ Gothenburg, Chalmers Univ Technol, Dept Math Sci, Gothenburg, Sweden..
    Sandegren, Linus
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinsk biokemi och mikrobiologi.
    Westerlund, Fredrik
    Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Ambjornsson, Tobias
    Lund Univ, Dept Astron & Theoret Phys, Lund, Sweden..
    Facilitated sequence assembly using densely labeled optical DNA barcodes: A combinatorial auction approach2018Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, nr 3, artikkel-id e0193900Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The output from whole genome sequencing is a set of contigs, i.e. short non-overlapping DNA sequences (sizes 1-100 kilobasepairs). Piecing the contigs together is an especially difficult task for previously unsequenced DNA, and may not be feasible due to factors such as the lack of sufficient coverage or larger repetitive regions which generate gaps in the final sequence. Here we propose a new method for scaffolding such contigs. The proposed method uses densely labeled optical DNA barcodes from competitive binding experiments as scaffolds. On these scaffolds we position theoretical barcodes which are calculated from the contig sequences. This allows us to construct longer DNA sequences from the contig sequences. This proof-of-principle study extends previous studies which use sparsely labeled DNA barcodes for scaffolding purposes. Our method applies a probabilistic approach that allows us to discard "foreign" contigs from mixed samples with contigs from different types of DNA. We satisfy the contig non-overlap constraint by formulating the contig placement challenge as a combinatorial auction problem. Our exact algorithm for solving this problem reduces computational costs compared to previous methods in the combinatorial auction field. We demonstrate the usefulness of the proposed scaffolding method both for synthetic contigs and for contigs obtained using Illumina sequencing for a mixed sample with plasmid and chromosomal DNA.

  • 50. Dyakova, O.
    et al.
    Mueller, M.M.
    Egelhaaf, M.
    Nordström, K.
    Predicting unconstrained field flight behaviour from image statisticsInngår i: Artikkel i tidsskrift (Fagfellevurdert)
12345 1 - 50 of 201
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