title: Analysis of the chemical toxicity effects using the enrichment of Gene Ontology terms and KEGG pathways.
abstract: Chemical toxicity is one of the major barriers for designing and detecting new chemical entities during drug discovery. Unexpected toxicity of an approved drug may lead to withdrawal from the market and significant loss of the associated costs. Better understanding of the mechanisms underlying various toxicity effects can help eliminate unqualified candidate drugs in early stages, allowing researchers to focus their attention on other more viable candidates.
  
  
  
  In this study, we aimed to understand the mechanisms underlying several toxicity effects using Gene Ontology (GO) terms and KEGG pathways. GO term and KEGG pathway enrichment theories were adopted to encode each chemical, and the minimum redundancy maximum relevance (mRMR) was used to analyze the GO terms and the KEGG pathways. Based on the feature list obtained by the mRMR method, the most related GO terms and KEGG pathways were extracted.
  
  
  
  Some important GO terms and KEGG pathways were uncovered, which were concluded to be significant for determining chemical toxicity effects.
  
  
  
  Several GO terms and KEGG pathways are highly related to all investigated toxicity effects, while some are specific to a certain toxicity effect.
  
  
  
  The findings in this study have the potential to further our understanding of different chemical toxicity mechanisms and to assist scientists in developing new chemical toxicity prediction algorithms. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.
authors.affiliation: College of Information Engineering, Shanghai Maritime University, Shanghai 201306, People's Republic of China. Electronic address: chen_lei1@163.com.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China. Electronic address: zhangyh825@163.com.
authors.forename: Yu-Hang
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Tianjin University, Tianjin 300072, People's Republic of China. Electronic address: zouquan@nclab.net.
authors.forename: Quan
authors.initials: Q
authors.lastname: Zou
authors.affiliation: Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China. Electronic address: chuchen@sibcb.ac.cn.
authors.forename: Chen
authors.initials: C
authors.lastname: Chu
authors.affiliation: State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, People's Republic of China. Electronic address: appo@xmu.edu.cn.
authors.forename: Zhiliang
authors.initials: Z
authors.lastname: Ji
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D055808:Drug Discovery; D063990:Gene Ontology; D004364:Pharmaceutical Preparations / Q000737:chemistry*
chemical_list: D004364:Pharmaceutical Preparations
keywords: Chemical toxicity effect; Enrichment score; Gene Ontology; KEGG pathway; Minimum redundancy maximum relevance