This paper proposes a scheme to predict whether a compound (1) is mainly stored within lipid tissues, (2) has additional storage sites (e.g., proteins), or (3) is metabolized/eliminated with a reduced bioconcentration. The approach is based on two validated QSAR (Quantitative Structure–Activity Relationship) trees, whose salient features are: (a) descriptor interpretability and (b) simplicity. Treeswere developed for 779 organic compounds, theTGD approach was used to quantify the lipid-driven bioconcentration, and a refined machine-learning optimization procedure was applied. Wefocused on molecular descriptor interpretation, which allowed us to gather new mechanistic insights into the bioconcentration mechanisms
Citazione: | Grisoni, F., Consonni, V., Vighi, M., Villa, S., & Todeschini, R. (2016). Investigating the mechanisms of bioconcentration through QSAR classification trees. ENVIRONMENT INTERNATIONAL, 88, 198-205. |
Tipo: | Articolo in rivista - Articolo scientifico |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | No |
Titolo: | Investigating the mechanisms of bioconcentration through QSAR classification trees |
Autori: | Grisoni, F; Consonni, V; Vighi, M; Villa, S; Todeschini, R |
Autori: | |
Data di pubblicazione: | 2016 |
Lingua: | English |
Rivista: | ENVIRONMENT INTERNATIONAL |
Digital Object Identifier (DOI): | 10.1016/j.envint.2015.12.024 |
Appare nelle tipologie: | 01 - Articolo su rivista |
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