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  ToxDB: pathway-level interpretation of drug-treatment data

Hardt, C., Beber, M. E., Rasche, A., Kamburov, A., Hebels, D. G., Kleinjans, J. C., et al. (2016). ToxDB: pathway-level interpretation of drug-treatment data. Database (Oxford), 2016: baw052. doi:10.1093/database/baw052.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-46F3-6 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-46F4-4
Genre: Journal Article

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© The Author(s) 2016

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 Creators:
Hardt, C.1, Author              
Beber, M. E.1, Author
Rasche, A.1, Author              
Kamburov, A.1, Author              
Hebels, D. G., Author
Kleinjans, J. C., Author
Herwig, R.1, Author              
Affiliations:
1Bioinformatics (Ralf Herwig), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2385701              

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 Abstract: MOTIVATION: 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.

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Language(s): eng - English
 Dates: 2016-03-172016-04-13
 Publication Status: Published online
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 Identifiers: PMID: 27074805
DOI: 10.1093/database/baw052
ISSN: 1758-0463 (Electronic)
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Title: Database (Oxford)
Source Genre: Journal
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Pages: - Volume / Issue: 2016 Sequence Number: baw052 Start / End Page: - Identifier: -