title: ToxDB: pathway-level interpretation of drug-treatment data.
abstract: BACKGROUND
  Extensive drug treatment gene expression data have been generated in order to identify biomarkers that are predictive for toxicity or to classify compounds. However, such patterns are often highly variable across compounds and lack robustness. We and others have previously shown that supervised expression patterns based on pathway concepts rather than unsupervised patterns are more robust and can be used to assess toxicity for entire classes of drugs more reliably.
  
  
  RESULTS
  We have developed a database, ToxDB, for the analysis of the functional consequences of drug treatment at the pathway level. We have collected 2694 pathway concepts and computed numerical response scores of these pathways for 437 drugs and chemicals and 7464 different experimental conditions. ToxDB provides functionalities for exploring these pathway responses by offering tools for visualization and differential analysis allowing for comparisons of different treatment parameters and for linking this data with toxicity annotation and chemical information.Database URL:http://toxdb.molgen.mpg.de.
authors.affiliation: Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr, 73, D-14195 Berlin, Germany.
authors.forename: C
authors.initials: C
authors.lastname: Hardt
authors.affiliation: Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr, 73, D-14195 Berlin, Germany.
authors.forename: M E
authors.initials: ME
authors.lastname: Beber
authors.affiliation: Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr, 73, D-14195 Berlin, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Rasche
authors.affiliation: Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr, 73, D-14195 Berlin, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Kamburov
authors.affiliation: Department of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, Md 6200, The Netherlands Department of Cell Biology-Inspired Tissue Engineering, MERLN Institute, Maastricht University, Universiteitssingel 40, Maastricht, Er 6229, The Netherlands.
authors.forename: D G
authors.initials: DG
authors.lastname: Hebels
authors.affiliation: Department of Toxicogenomics, School of Oncology and Developmental Biology (GROW), Maastricht University, Maastricht, Md 6200, The Netherlands.
authors.forename: J C
authors.initials: JC
authors.lastname: Kleinjans
authors.affiliation: Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr, 73, D-14195 Berlin, Germany herwig@molgen.mpg.de.
authors.forename: R
authors.initials: R
authors.lastname: Herwig
mesh_terms: D000818:Animals; D019295:Computational Biology; D030541:Databases, Genetic; D062313:Databases, Pharmaceutical; D015870:Gene Expression / Q000187:drug effects*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020407:Internet; D010600:Pharmacology; D051381:Rats; D015398:Signal Transduction / Q000187:drug effects