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CORAL: Building up QSAR models for the chromosome aberration test

A high level of chromosomal aberrations in peripheral blood lymphocytes may be an early marker of cancer risk, but data on risk of specific cancers and types of chromosomal aberrations are limited. Consequently, the development of predictive models for chromosomal aberrations test is important task....

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Autores principales: Toropov, Andrey A., Toropova, Alla P., Raitano, Giuseppa, Benfenati, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6734133/
https://www.ncbi.nlm.nih.gov/pubmed/31516335
http://dx.doi.org/10.1016/j.sjbs.2018.05.013
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author Toropov, Andrey A.
Toropova, Alla P.
Raitano, Giuseppa
Benfenati, Emilio
author_facet Toropov, Andrey A.
Toropova, Alla P.
Raitano, Giuseppa
Benfenati, Emilio
author_sort Toropov, Andrey A.
collection PubMed
description A high level of chromosomal aberrations in peripheral blood lymphocytes may be an early marker of cancer risk, but data on risk of specific cancers and types of chromosomal aberrations are limited. Consequently, the development of predictive models for chromosomal aberrations test is important task. Majority of models for chromosomal aberrations test are so-called knowledge-based rules system. The CORAL software (http://www.insilico.eu/coral, abbreviation of “CORrelation And Logic”) is an alternative for knowledge-based rules system. In contrast to knowledge-based rules system, the CORAL software gives possibility to estimate the influence upon the predictive potential of a model of different molecular alerts as well as different splits into the training set and validation set. This possibility is not available for the approaches based on the knowledge-based rules system. Quantitative Structure–Activity Relationships (QSAR) for chromosome aberration test are established for five random splits into the training, calibration, and validation sets. The QSAR approach is based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) without data on physicochemical and/or biochemical parameters. In spite of this limitation, the statistical quality of these models is quite good.
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spelling pubmed-67341332019-09-12 CORAL: Building up QSAR models for the chromosome aberration test Toropov, Andrey A. Toropova, Alla P. Raitano, Giuseppa Benfenati, Emilio Saudi J Biol Sci Article A high level of chromosomal aberrations in peripheral blood lymphocytes may be an early marker of cancer risk, but data on risk of specific cancers and types of chromosomal aberrations are limited. Consequently, the development of predictive models for chromosomal aberrations test is important task. Majority of models for chromosomal aberrations test are so-called knowledge-based rules system. The CORAL software (http://www.insilico.eu/coral, abbreviation of “CORrelation And Logic”) is an alternative for knowledge-based rules system. In contrast to knowledge-based rules system, the CORAL software gives possibility to estimate the influence upon the predictive potential of a model of different molecular alerts as well as different splits into the training set and validation set. This possibility is not available for the approaches based on the knowledge-based rules system. Quantitative Structure–Activity Relationships (QSAR) for chromosome aberration test are established for five random splits into the training, calibration, and validation sets. The QSAR approach is based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) without data on physicochemical and/or biochemical parameters. In spite of this limitation, the statistical quality of these models is quite good. Elsevier 2019-09 2018-05-09 /pmc/articles/PMC6734133/ /pubmed/31516335 http://dx.doi.org/10.1016/j.sjbs.2018.05.013 Text en © 2018 King Saud University http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Toropov, Andrey A.
Toropova, Alla P.
Raitano, Giuseppa
Benfenati, Emilio
CORAL: Building up QSAR models for the chromosome aberration test
title CORAL: Building up QSAR models for the chromosome aberration test
title_full CORAL: Building up QSAR models for the chromosome aberration test
title_fullStr CORAL: Building up QSAR models for the chromosome aberration test
title_full_unstemmed CORAL: Building up QSAR models for the chromosome aberration test
title_short CORAL: Building up QSAR models for the chromosome aberration test
title_sort coral: building up qsar models for the chromosome aberration test
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6734133/
https://www.ncbi.nlm.nih.gov/pubmed/31516335
http://dx.doi.org/10.1016/j.sjbs.2018.05.013
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