Automated detection of structural alerts (chemical fragments) in (eco)toxicology - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Computational and Structural Biotechnology Journal Année : 2013

Automated detection of structural alerts (chemical fragments) in (eco)toxicology

Résumé

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.
Fichier principal
Vignette du fichier
RIACL-LEPAILLEUR-2013-1.pdf (1.9 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-01023826 , version 1 (15-07-2014)

Identifiants

Citer

Alban Lepailleur, Guillaume Poezevara, Ronan Bureau. Automated detection of structural alerts (chemical fragments) in (eco)toxicology. Computational and Structural Biotechnology Journal, 2013, 5 (6), pp.e201302013. ⟨10.5936/csbj.201302013⟩. ⟨hal-01023826⟩
118 Consultations
49 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More