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eMolTox: prediction of molecular toxicity with confidence

Ji, C; Svensson, F; Zoufir, A; Bender, A; (2018) eMolTox: prediction of molecular toxicity with confidence. Bioinformatics , 34 (14) pp. 2508-2509. 10.1093/bioinformatics/bty135. Green open access

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Abstract

In this work, we present eMolTox, a web server for the prediction of potential toxicity associated with a given molecule. A total of 174 toxicology-related in vitro/vivo experimental datasets were used for model construction and Mondrian conformal prediction was used to estimate the confidence of the resulting predictions. Toxic substructure analysis is also implemented in eMolTox. eMolTox predicts and displays a wealth of information of potential molecular toxicities for safety analysis in drug development.

Type: Article
Title: eMolTox: prediction of molecular toxicity with confidence
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bioinformatics/bty135
Publisher version: https://doi.org/10.1093/bioinformatics/bty135
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/10062387
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