Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Lepailleur, Alban, Poezevara, Guillaume, Bureau, Ronan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology (RNCSB) Organization 2013
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
_version_ 1782308400105783296
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
work_keys_str_mv AT lepailleuralban automateddetectionofstructuralalertschemicalfragmentsinecotoxicology
AT poezevaraguillaume automateddetectionofstructuralalertschemicalfragmentsinecotoxicology
AT bureauronan automateddetectionofstructuralalertschemicalfragmentsinecotoxicology