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Visualizing bacterial tRNA identity determinants and antideterminants using function logos and inverse function logos
Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, The Linnaeus Centre for Bioinformatics.
2006 In: Nucleic Acids Research, ISSN 0305-1048, Vol. 34, no 3, 905-916 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2006. Vol. 34, no 3, 905-916 p.
Identifiers
URN: urn:nbn:se:uu:diva-96428OAI: oai:DiVA.org:uu-96428DiVA: diva2:170997
Available from: 2007-11-13 Created: 2007-11-13Bibliographically approved
In thesis
1. A Study in RNA Bioinformatics: Identification, Prediction and Analysis
Open this publication in new window or tab >>A Study in RNA Bioinformatics: Identification, Prediction and Analysis
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research in the last few decades has revealed the great capacity of the RNA molecule. RNA, which previously was assumed to play a main role only as an intermediate in the translation of genes to proteins, is today known to play many important roles in the cell in addition to that as a messenger RNA and transfer RNA, including the ability to catalyze reactions and gene regulations at various levels.

This thesis investigates several computational aspects of RNA. We will discuss identification of novel RNAs and RNAs that are known to exist in related species, RNA secondary structure prediction, as well as more general tools for analyzing, visualizing and classifying RNA sequences.

We present two benchmark studies concerning RNA identification, both de novo identification/characterization of single RNA sequences and homology search methods.

We develope a novel algorithm for analysis of the RNA folding landscape that is based on the nearest neighbor energy model adopted in many secondary structure prediction programs. We implement this algorithm, which computes structural neighbors of a given RNA secondary structure, in the program RNAbor, which is accessible on a web server.

Furthermore, we combine a mutual information based structure prediction algorithm with a sequence logo visualization to create a novel visualization tool for analyzing an RNA alignment and identifying covarying sites.

Finally, we present extensions to sequence logos for the purpose of tRNA identity analysis. We introduce function logos, which display features that distinguish functional subclasses within a large set of structurally related sequences, as well as the inverse logos, which display underrepresented features. For the purpose of comparing tRNA identity elements between different taxa we introduce two contrasting logos, the information difference and the Kullback-Leibler divergence difference logos.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2007. 75 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 364
Keyword
RNA, bioinformatics, secondary structure, structure prediction, dynamic programming, energy landscape, homology search, sequence logo, tRNA
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-8305 (URN)978-91-554-7019-7 (ISBN)
Public defence
2007-12-07, B42, BMC, Husargatan 3, Uppsala, 13:00
Opponent
Supervisors
Available from: 2007-11-13 Created: 2007-11-13Bibliographically approved

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