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Automated detection of structural alerts (chemical fragments) in (eco)toxicology
This mini-review describes the evolution of different algorithms dedicated to the automated discovery of chemical fragments associated to (eco)toxicological endpoints. These structural alerts correspond to one of the most interesting approach of in silico toxicology due to their direct link with spe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology (RNCSB) Organization
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962211/ https://www.ncbi.nlm.nih.gov/pubmed/24688706 http://dx.doi.org/10.5936/csbj.201302013 |
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author | Lepailleur, Alban Poezevara, Guillaume Bureau, Ronan |
author_facet | Lepailleur, Alban Poezevara, Guillaume Bureau, Ronan |
author_sort | Lepailleur, Alban |
collection | PubMed |
description | This mini-review describes the evolution of different algorithms dedicated to the automated discovery of chemical fragments associated to (eco)toxicological endpoints. These structural alerts correspond to one of the most interesting approach of in silico toxicology due to their direct link with specific toxicological mechanisms. A number of expert systems are already available but, since the first work in this field which considered a binomial distribution of chemical fragments between two datasets, new data miners were developed and applied with success in chemoinformatics. The frequency of a chemical fragment in a dataset is often at the core of the process for the definition of its toxicological relevance. However, recent progresses in data mining provide new insights into the automated discovery of new rules. Particularly, this review highlights the notion of Emerging Patterns that can capture contrasts between classes of data. |
format | Online Article Text |
id | pubmed-3962211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Research Network of Computational and Structural Biotechnology (RNCSB) Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-39622112014-03-31 Automated detection of structural alerts (chemical fragments) in (eco)toxicology Lepailleur, Alban Poezevara, Guillaume Bureau, Ronan Comput Struct Biotechnol J Mini Reviews This mini-review describes the evolution of different algorithms dedicated to the automated discovery of chemical fragments associated to (eco)toxicological endpoints. These structural alerts correspond to one of the most interesting approach of in silico toxicology due to their direct link with specific toxicological mechanisms. A number of expert systems are already available but, since the first work in this field which considered a binomial distribution of chemical fragments between two datasets, new data miners were developed and applied with success in chemoinformatics. The frequency of a chemical fragment in a dataset is often at the core of the process for the definition of its toxicological relevance. However, recent progresses in data mining provide new insights into the automated discovery of new rules. Particularly, this review highlights the notion of Emerging Patterns that can capture contrasts between classes of data. Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2013-04-06 /pmc/articles/PMC3962211/ /pubmed/24688706 http://dx.doi.org/10.5936/csbj.201302013 Text en © Lepailleur et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. |
spellingShingle | Mini Reviews Lepailleur, Alban Poezevara, Guillaume Bureau, Ronan Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title | Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title_full | Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title_fullStr | Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title_full_unstemmed | Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title_short | Automated detection of structural alerts (chemical fragments) in (eco)toxicology |
title_sort | automated detection of structural alerts (chemical fragments) in (eco)toxicology |
topic | Mini Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3962211/ https://www.ncbi.nlm.nih.gov/pubmed/24688706 http://dx.doi.org/10.5936/csbj.201302013 |
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