کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8553889 | 1562696 | 2018 | 31 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
CON4EI: Evaluation of QSAR models for hazard identification and labelling of eye irritating chemicals
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم محیط زیست
بهداشت، سم شناسی و جهش زایی
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چکیده انگلیسی
For three computational models (Toxtree, and Case Ultra EYE_DRAIZE and EYE_IRR) performance parameters were calculated. Coverage ranged from 15 to 58%. Coverage was 2 to 3.4 times higher for liquids than for solids. The lowest number of false positives (5%) was reached with EYE_IRR; this model however also gave a high number of false negatives (46%). The lowest number of false negatives (25%) was seen with Toxtree; for liquids Toxtree predicted the lowest number of false negatives (11%), for solids EYE_DRAIZE did (17%). It can be concluded that the training sets should be enlarged with high quality data. The tested models are not yet sufficiently powerful for stand-alone evaluations, but that they can surely become of value in an integrated weight-of-evidence approach in hazard assessment.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Toxicology in Vitro - Volume 49, June 2018, Pages 90-98
Journal: Toxicology in Vitro - Volume 49, June 2018, Pages 90-98
نویسندگان
L. Geerts, E. Adriaens, N. Alépée, R. Guest, J.A. Sr, H. Kandarova, A. Drzewiecka, P. Fochtman, S. Verstraelen, A.R. Van Rompay,