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Comparing the Landcapes of Common Retroviral Insertion Sites across Tumor Models
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
Malardalen Univ, Sch Educ Culture & Commun UKK, Div Appl Math, Box 883, S-72123 Vasteras, Sweden..
Malardalen Univ, Sch Educ Culture & Commun UKK, Div Appl Math, Box 883, S-72123 Vasteras, Sweden..ORCID iD: 0000-0003-4554-6528
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2017 (English)In: ICNPAA 2016 WORLD CONGRESS: 11TH INTERNATIONAL CONFERENCE ON MATHEMATICAL PROBLEMS IN ENGINEERING, AEROSPACE AND SCIENCES / [ed] Sivasundaram, S, AMER INST PHYSICS , 2017, 020173Conference paper (Refereed)
Abstract [en]

Retroviral tagging represents an important technique, which allows researchers to screen for candidate cancer genes. The technique is based on the integration of retroviral sequences into the genome of a host organism, which might then lead to the artificial inhibition or expression of proximal genetic elements. The identification of potential cancer genes in this framework involves the detection of genomic regions (common insertion sites; CIS) which contain a number of such viral integration sites that is greater than expected by chance. During the last two decades, a number of different methods have been discussed for the identification of such loci and the respective techniques have been applied to a variety of different retroviruses and/or tumor models. We have previously established a retrovirus driven brain tumor model and reported the CISs which were found based on a Monte Carlo statistics derived detection paradigm. In this study, we consider a recently proposed alternative graph theory based method for identifying CISs and compare the resulting CIS landscape in our brain tumor dataset to those obtained when using the Monte Carlo approach. Finally, we also employ the graph-based method to compare the CIS landscape in our brain tumor model with those of other published retroviral tumor models.

Place, publisher, year, edition, pages
AMER INST PHYSICS , 2017. 020173
Series
AIP Conference Proceedings, ISSN 0094-243X ; 1798
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-322307DOI: 10.1063/1.4972765ISI: 000399203000172ISBN: 978-0-7354-1464-8 (electronic)OAI: oai:DiVA.org:uu-322307DiVA: diva2:1096762
Conference
11th International Conference on Mathematical Problems in Engineering, Aerospace and Sciences (ICNPAA), JUL 04-08, 2016, Univ La Rochelle, La Rochelle, FRANCE
Funder
Swedish Childhood Cancer Foundation
Available from: 2017-05-19 Created: 2017-05-19 Last updated: 2017-05-19Bibliographically approved

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Weishaupt, HolgerČančer, MatkoSilvestrov, SergeiSwartling, Fredrik J
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