Inferring disease-related pathways using a probabilistic epistasis model.
Inferring disease-related pathways using a probabilistic epistasis model.
复制标题
使用概率上位模型推断疾病相关途径。
DOI：
10.1142/9789812836939_0046
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发表时间：
2009
影响因子：
--
通讯作者：
Stuart,JM
中科院分区：
文献类型：
--
作者：
Kanabar,PN;Vaske,CJ;Yeang,CH;Yildiz,FH;Stuart,JM
Motivation: We present a probabilistic model called a Joint Intervention Network (JIN) for inferring interactions among a chosen set of regulator genes. The input to the method are expression changes of downstream indicator genes observed under the knock-out of the regulators. JIN can use any number of perturbation combinations for model inference (e.g. single, double, and triple knock-outs).Results/Conclusions: We applied JIN to aVibrio choleraeregulatory network to uncover mechanisms critical to its environmental persistence.V. choleraeis a facultative human pathogen that causes cholera in humans and responsible for seven pandemics. We analyzed the expression response of 17V. choleraebiofilm indicator genes under various single and multiple knock-outs of three known biofilm regulators. Using the inferred network, we were able to identify new genes involved in biofilm formation more accurately than clustering expression profiles.
