A novel method of using Deep Belief Networks and genetic perturbation data to search for yeast signaling pathways.

ABSTRACT: Perturbing a signaling system with a serial of single gene deletions and then observing corresponding expression changes in model organisms, such as yeast, is an important and widely used experimental technique for studying signaling pathways. People have developed different computational methods to analyze the perturbation data from gene deletion experiments for exploring the signaling pathways. The most popular methods/techniques include K-means clustering and hierarchical clustering techniques, or combining the expression data with knowledge, such as protein-protein interactions (PPIs) or gene ontology (GO), to search for new pathways. However, these methods neither consider nor fully utilize the intrinsic relation between the perturbation of a pathway and expression changes of genes re

SUBMITTER: Lu S 

PROVIDER: S-EPMC6135403 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature