1453913
doi
10.5281/zenodo.1453913
oai:zenodo.org:1453913
Gilberg, Erik
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Blaschke, Thomas
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Bajorath, Jürgen
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Distinguishing between pan assay interference compounds (PAINS) that are promiscuous or represent dark chemical matter - data set and prediction models
Jasial, Swarit
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Pan Assay Interference Compounds (PAINS)
Dark Chemical Matter (DCM)
Support Vector Machines (SVM)
<p>Data sets of promiscuous PAINS (PROM_PAINS) and dark chemical matter PAINS (DCM_PAINS) are provided and support vector machine models built on the basis of original and balanced training data (see readme.txt).<br>
</p>
Zenodo
2018-10-10
info:eu-repo/semantics/other
1453912
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