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Cassotti, M.* ; Ballabio, D.* ; Consonni, V.* ; Mauri, A.* ; Tetko, I.V. ; Todeschini, R.*

Prediction of acute aquatic toxicity toward Daphnia magna by using the GA-kNN method.

ATLA-Altern. Lab. Anim. 42, 31-41 (2014)
Verlagsversion Volltext
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In this study, a QSAR model was developed from a data set consisting of 546 organic molecules, to predict acute aquatic toxicity toward Daphnia magna. A modified k-Nearest Neighbour (kNN) strategy was used as the regression method, which provided prediction only for those molecules with an average distance from the k nearest neighbours lower than a selected threshold. The final model showed good performance (R(2) and Q(2) cv equal to 0.78, Q(2) ext equal to 0.72). It comprised eight molecular descriptors that encoded information about lipophilicity, the formation of H-bonds, polar surface area, polarisability, nucleophilicity and electrophilicity.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Aquatic Toxicity ; Daphnia Magna ; Genetic Algorithms ; Knn ; Qsar; Quantitative Structure; Qsar Models; Organic-compounds; Classification; Environment; Chemicals; (benzo)triazoles; Pharmaceuticals; Prioritization; Antibiotics
ISSN (print) / ISBN 0261-1929
Quellenangaben Band: 42, Heft: 1, Seiten: 31-41 Artikelnummer: , Supplement: ,
Verlag Sage
Verlagsort North Sherwood St, Nottingham
Begutachtungsstatus Peer reviewed