Understanding Gene Sequence Variation in the Context of Transcription Regulation in Yeast

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The availability of expression quantitative trait loci (eQTL) data can help understanding the genetic basis of variation in gene expression. However, it has proven difficult to accurately predict functional genetic changes due to low statistical power. To address this challenge, we developed a novel computational approach for combining eQTL data with complementary regulatory network to identify modules of genes, their underlying genetic polymorphism and their shared regulatory proteins activity. The resulting eQTL model implicates novel central protein complexes that share not only a regulatory protein but also an underlying genetic variation. Our method manifests higher sensitivity than prior computational efforts.

Original languageEnglish
Title of host publicationResearch in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
EditorsVineet Bafna, S. Cenk Sahinalp
PublisherSpringer Verlag
Pages69
Number of pages1
ISBN (Print)9783642200359
DOIs
StatePublished - 2011
Event15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, BC, Canada
Duration: 28 Mar 201131 Mar 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6577 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
Country/TerritoryCanada
CityVancouver, BC
Period28/03/1131/03/11

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