Sherhod, R., Gillet, V.J., Judson, P.N. et al. (1 more author) (2012) Automating Knowledge Discovery for Toxicity Prediction Using Jumping Emerging Pattern Mining. Journal of Chemical and Information Modeling, 52 (11). 3074 - 3087. ISSN 1549-9596
Abstract
: The design of new alerts, that is, collections of structural features observed to result in toxicological activity, can be a slow process and may require significant input from toxicology and chemistry experts. A method has therefore been developed to help automate alert identification by mining descriptions of activating structural features directly from toxicity data sets. The method is based on jumping emerging pattern mining which is applied to a set of toxic and nontoxic compounds that are represented using atom pair descriptors. Using the resulting jumping emerging patterns, it is possible to cluster toxic compounds into groups defined by the presence of shared structural features and to arrange the clusters into hierarchies. The methodology has been tested on a number of data sets for Ames mutagenicity, oestrogenicity, and hERG channel inhibition end points. These tests have shown the method to be effective at clustering the data sets around minimal jumping-emerging structural patterns and finding descriptions of potentially activating structural features. Furthermore, the mined structural features have been shown to be related to some of the known alerts for all three tested end points.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012.Richard Sherhod, Valerie J. Gillet, Philip N. Judson, and Jonathan D. Vessey . This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Jul 2015 08:20 |
Last Modified: | 07 Jul 2015 08:21 |
Published Version: | http://dx.doi.org/10.1021/ci300254w |
Status: | Published |
Publisher: | American Chemical Society |
Refereed: | Yes |
Identification Number: | 10.1021/ci300254w |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:87576 |