Literature DB >> 23368100

CORAL: classification model for predictions of anti-sarcoma activity.

A A Toropov1, A P Toropova, E Benfenati, G Gini, D Leszczynska, J Leszczynski.   

Abstract

A modified version of the CORAL software (http://www.insilico.eu/coral) allows building up the classification model for the case of the Yes/No data on the anti-sarcoma activity of organic compounds. Three random splits into the sub-training, calibration, and test sets of the data for 3017 compounds were examined. The performance of the proposed approach is satisfactory. The average values of the statistical characteristics for external test set on three random splits are as follows: n=1173-1234, sensitivity = 0.8903±0.0390, specificity = 0.9869±0.0013, and accuracy = 0.9759±0.0043. Mechanistic interpretation of the suggested model is discussed.

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Year:  2012        PMID: 23368100     DOI: 10.2174/1568026611212240004

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  2 in total

1.  Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors.

Authors:  Apilak Worachartcheewan; Virapong Prachayasittikul; Alla P Toropova; Andrey A Toropov; Chanin Nantasenamat
Journal:  Mol Divers       Date:  2015-11       Impact factor: 2.943

2.  CORAL: Building up QSAR models for the chromosome aberration test.

Authors:  Andrey A Toropov; Alla P Toropova; Giuseppa Raitano; Emilio Benfenati
Journal:  Saudi J Biol Sci       Date:  2018-05-09       Impact factor: 4.219

  2 in total

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