کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
575644 | 1453057 | 2016 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction
ترجمه فارسی عنوان
یک رابطه فعالیت ساختاری کمی برای سمیت حاد سمی از آفت کش ها در موش صحرایی: اعتبار سنجی، دامنه کاربرد و پیش بینی
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کلمات کلیدی
ANNLD50BFGSOECDMLPRMSVIFpesticides - آفتکشهاExternal validation - اعتبار خارجیCross-validation - اعتبار سنجی متقابلQSAR - بزرگسال leave-one-out - ترک یکregistration, evaluation, authorization and restriction of chemicals - ثبت نام، ارزیابی، مجوز و محدودیت مواد شیمیاییapplicability domain - دامنه کاربردlethal dose 50 - دوز مرگبار 50Quantitative structure–activity relationship - رابطه ساختاری و فعالیت کمیREACH - رسیدنRoot mean square error - ریشه میانگین خطای مربعOrganization for Economic Cooperation and Development - سازمان همکاری های اقتصادی و توسعهAcute toxicity - سمیت حادartificial neural networks - شبکه های عصبی مصنوعیLOO - لئوPrediction - پیش بینیMulti-Layer Perceptron - چند لایه ی Perceptron
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بهداشت و امنیت شیمی
چکیده انگلیسی
Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q2ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hazardous Materials - Volume 303, 13 February 2016, Pages 28-40
Journal: Journal of Hazardous Materials - Volume 303, 13 February 2016, Pages 28-40
نویسندگان
Mabrouk Hamadache, Othmane Benkortbi, Salah Hanini, Abdeltif Amrane, Latifa Khaouane, Cherif Si Moussa,