Premium
Understanding Gene Regulatory Networks and Their Variations
Author(s) -
Koller Daphne
Publication year - 2010
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.24.1_supplement.81.2
Subject(s) - gene regulatory network , expression quantitative trait loci , biology , computational biology , population , gene , selection (genetic algorithm) , regulation of gene expression , gene expression , computer science , genetics , artificial intelligence , demography , sociology , genotype , single nucleotide polymorphism
A key biological question is to uncover the regulatory networks in a cellular system and to understand how this network varies across individuals, cell types, and environmental conditions. In this talk I will describe work that uses statistical learning techniques to address this goal. Specifically, I will show how gene expression data from a population of genetically diverse individuals (eQTL data) can be used both to uncover regulatory networks and to understand the mechanisms by which genetic variations perturbs those networks. We also show how a prior knowledge and data regarding biological networks and mechanisms can be used to guide the construction of regulatory networks and allow the robust selection of genetic variations that are causal for phenotypic change. I will also show how gene expression from a collection of diverse cell types can be used to understand the role of gene regulation in immune cell differentiation.