@inproceedings{5a3d1ec113944c26bd660916bc3be737,
title = "A novel probabilistic methodology for eQTL analysis of signaling networks",
abstract = "Quantitative trait loci (QTL) studies of common diseases have been spectacularly successful in the last few years and became routine in medical genetics. These studies typically identify genetic variants (QTLs) that are associated with organismal phenotypes, such as susceptibility to disease. Genetic variants can underlie the abundance of gene transcripts, forming {\textquoteleft}expression QTLs{\textquoteright} (eQTLs; [1]). Despite the biomedical importance of understanding how such loci truly affect quantitative traits, several questions remain unsolved: What is the particular mechanism by which a genomic locus affects a quantitative trait? Which specific signaling pathways are responsible for propagating the inherited variation from an eQTL to the gene expression or physiological trait? On which component within such a pathway does the genetic variant act? While it is clear that genetic variants play a critical role in quantitative traits, it is still not fully understood how such variants lead to the inherited variation.",
author = "Roni Wilentzik and Irit Gat-Viks",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015 ; Conference date: 12-04-2015 Through 15-04-2015",
year = "2015",
doi = "10.1007/978-3-319-16706-0_34",
language = "الإنجليزيّة",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "338--339",
editor = "Przytycka, {Teresa M.}",
booktitle = "Research in Computational Molecular Biology - 19th Annual International Conference, RECOMB 2015, Proceedings",
address = "ألمانيا",
}