Toxicity Analysis of Pentachlorophenol Data with a Bioinformatics Tool Set

Rapid progress in technologies opened the new era of computer-leaded analytics, leaving humans more space for experimental design and decision making. Here we demonstrate the machine learning analysis workflow represented by spectral clustering, elucidation of evolutionary conserved transcription regulation, and network analysis using reverse engineering. Analysis of genes induced by the Pentachlorophenol toxic chemical revealed two subnetworks, one orchestrated by Interferon and another by Nuclear receptor factor 2 (NRF2) gene. Furthermore, network-inference based analysis identified a gene network module composed of genes associated with interferon signaling and their regulatory interaction with downstream genes, especially TRIM family proteins involved in responses of innate immune systems.