MolClass: a web portal to interrogate diverse small molecule screen datasets with different computational models

Jan Wildenhain, Nicholas Fitzgerald, Mike Tyers

Research output: Contribution to journalArticlepeer-review

Abstract

Summary: The MolClass toolkit and data portal generates computa-tional models from user-defined small molecule datasets based on structural features identified in hit and non-hit molecules in different screens. Each new model is applied to all datasets in the database to classify compound specificity. MolClass thus defines a likelihood value for each compound entry and creates an activity fingerprint across diverse sets of screens. MolClass uses a variety of machine-learning methods to find molecular patterns, and can therefore also assign a priori predictions of bioactivities for previously untested molecules. The power of the MolClass resource will grow as a function of the number of screens deposited in the database.
Availability and implementation: The MolClass webportal, software package and source code is freely available for non-commercial use at http://tyerslab.bio.ed.ac.uk/molclass. A MolClass tutorial and a guide on how to build models from datasets can also be found on the website. MolClass uses the chemistry development kit (CDK), WEKA and MySQL for its core functionality. A REST service is available at http://tyerslab.bio.ed.ac.uk/molclass/api based on the OpenTox API 1.2.
Contact: jan.wildenhain@ed.ac.uk, md.tyers@umontreal.ca.
Original languageEnglish
Pages (from-to)2200-2201
Number of pages2
JournalBioinformatics
Volume28
Issue number16
Early online date17 Jun 2012
DOIs
Publication statusPublished - 15 Aug 2012

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