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Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.

The most important criteria for the development and analysis of databases for elucidating the structural bases of toxicological activity include the integrity of the databases with respect to uniformity of the experimental protocol and interpretation of the test results and inclusion of chemicals re...

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Detalles Bibliográficos
Autores principales: Klopman, G, Rosenkranz, H
Formato: Texto
Lenguaje:English
Publicado: 1991
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1568254/
https://www.ncbi.nlm.nih.gov/pubmed/1820281
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author Klopman, G
Rosenkranz, H
author_facet Klopman, G
Rosenkranz, H
author_sort Klopman, G
collection PubMed
description The most important criteria for the development and analysis of databases for elucidating the structural bases of toxicological activity include the integrity of the databases with respect to uniformity of the experimental protocol and interpretation of the test results and inclusion of chemicals representing different chemical classes and differing mechanisms of action. Within these criteria, it is demonstrated that when the chemicals are chosen at random, the larger the database, the better the predictivity of chemicals not included in the learning set. It is shown however, that when chemicals are selected on the basis of structural features, that a learning set of approximately 180 chemicals is as informative as a database consisting of 800 chemicals chosen at random.
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spelling pubmed-15682542006-09-18 Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases. Klopman, G Rosenkranz, H Environ Health Perspect Research Article The most important criteria for the development and analysis of databases for elucidating the structural bases of toxicological activity include the integrity of the databases with respect to uniformity of the experimental protocol and interpretation of the test results and inclusion of chemicals representing different chemical classes and differing mechanisms of action. Within these criteria, it is demonstrated that when the chemicals are chosen at random, the larger the database, the better the predictivity of chemicals not included in the learning set. It is shown however, that when chemicals are selected on the basis of structural features, that a learning set of approximately 180 chemicals is as informative as a database consisting of 800 chemicals chosen at random. 1991-12 /pmc/articles/PMC1568254/ /pubmed/1820281 Text en
spellingShingle Research Article
Klopman, G
Rosenkranz, H
Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title_full Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title_fullStr Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title_full_unstemmed Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title_short Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
title_sort structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1568254/
https://www.ncbi.nlm.nih.gov/pubmed/1820281
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