Article
Increasing the power to detect causal associations by combining genotypic and expression data in segregating populations.
PLoS computational biology - 13 Apr 2007
Zhu Jun, Wiener Matthew C, Zhang Chunsheng, Fridman Arthur, Minch Eric, Lum Pek Y, Sachs Jeffrey R, Schadt Eric E
Abstract excerpt
To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships...
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