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Model building in Bioclipse Decision Support applied to open datasets
AstraZeneca R&D.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0002-8083-2864
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
AstraZeneca R&D.
2012 (English)In: Toxicology Letters, ISSN 0378-4274, E-ISSN 1879-3169, Vol. 211, no Suppl., S62- p.Article in journal, Meeting abstract (Refereed) Published
Abstract [en]

Bioclipse Decision Support (DS) is a system capable of building predictive models of any collection of SAR data, and making them available in a simple user interface based on Bioclipse (www.bioclipse.net).

The method is fast and uses Faulon Signatures as chemical descriptors together with a Support Vector Machine algorithm for QSAR model building. A key feature is the capability to visualize and interpret results by highlighting the substructures which contributed most to the prediction. This, together with very fast predictions, allows for editing chemical structures with instantly updated results.

We here present the results from applying Bioclipse Decision Support to several open QSAR data sets, including endpoints from OpenTox and PubChem. The results show how to extract data from the sources and to build models which can be integrated with user specific models.

Place, publisher, year, edition, pages
2012. Vol. 211, no Suppl., S62- p.
National Category
Bioinformatics and Systems Biology
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-197845DOI: 10.1016/j.toxlet.2012.03.243OAI: oai:DiVA.org:uu-197845DiVA: diva2:614507
Conference
The 48th Congress of the European Societies of Toxicology, EUROTOX, 17-20 June, 2012, Stockholm, Sweden
Available from: 2013-04-04 Created: 2013-04-04 Last updated: 2017-12-06Bibliographically approved

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Publisher's full texthttp://www.sciencedirect.com/science/article/pii/S0378427412003451

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Spjuth, OlaEklund, Martin

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