title: Applying network analysis and Nebula (neighbor-edges based and unbiased leverage algorithm) to ToxCast data.
abstract: BACKGROUND
  ToxCast data have been used to develop models for predicting in vivo toxicity. To predict the in vivo toxicity of a new chemical using a ToxCast data based model, its ToxCast bioactivity data are needed but not normally available. The capability of predicting ToxCast bioactivity data is necessary to fully utilize ToxCast data in the risk assessment of chemicals.
  
  
  OBJECTIVE
  We aimed to understand and elucidate the relationships between the chemicals and bioactivity data of the assays in ToxCast and to develop a network analysis based method for predicting ToxCast bioactivity data.
  
  
  METHODS
  We conducted modularity analysis on a quantitative network constructed from ToxCast data to explore the relationships between the assays and chemicals. We further developed Nebula (neighbor-edges based and unbiased leverage algorithm) for predicting ToxCast bioactivity data.
  
  
  RESULTS
  Modularity analysis on the network constructed from ToxCast data yielded seven modules. Assays and chemicals in the seven modules were distinct. Leave-one-out cross-validation yielded a Q(2) of 0.5416, indicating ToxCast bioactivity data can be predicted by Nebula. Prediction domain analysis showed some types of ToxCast assay data could be more reliably predicted by Nebula than others.
  
  
  CONCLUSIONS
  Network analysis is a promising approach to understand ToxCast data. Nebula is an effective algorithm for predicting ToxCast bioactivity data, helping fully utilize ToxCast data in the risk assessment of chemicals.
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Ye
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Heng
authors.initials: H
authors.lastname: Luo
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Hui Wen
authors.initials: HW
authors.lastname: Ng
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Joe
authors.initials: J
authors.lastname: Meehan
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Weigong
authors.initials: W
authors.lastname: Ge
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
authors.forename: Weida
authors.initials: W
authors.lastname: Tong
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA. Electronic address: huixiao.hong@fda.hhs.gov.
authors.forename: Huixiao
authors.initials: H
authors.lastname: Hong
mesh_terms: D000465:Algorithms; D001681:Biological Assay; D054750:Ecotoxicology / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D018570:Risk Assessment; D018675:Toxicity Tests
keywords: Environmental toxicity; Nebula; Network algorithm; ToxCast