Predicting Toxicities of Diverse Chemical Pesticides in Multiple Avian Species Using Tree-Based QSAR Approaches for Regulatory Purposes-Reference-Cited by-同舟云学术

Predicting Toxicities of Diverse Chemical Pesticides in Multiple Avian Species Using Tree-Based QSAR Approaches for Regulatory Purposes

Published:2015-07-09 Issue:7 Volume:55 Page:1337-1348
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Basant Nikita¹,Gupta Shikha²,Singh Kunwar P.²

Affiliation:

1. Kan Ban Systems Pvt. Ltd., Laxmi Nagar, Delhi 110092, India

2. Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow, Uttar Pradesh 226 001, India

Funder

Council of Scientific and Industrial Research

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.5b00139

Reference71 articles.

1. QSTR Modeling for Qualitative and Quantitative Toxicity Predictions of Diverse Chemical Pesticides in Honey Bee for Regulatory Purposes

2. Impact of pesticides use in agriculture: their benefits and hazards

3. Pesticides and human chronic diseases: Evidences, mechanisms, and perspectives

4. A QSAR Study of Avian Oral Toxicity using Support Vector Machines and Genetic Algorithms

5. In silico prediction of chemical toxicity on avian species using chemical category approaches

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