Literature DB >> 11599929

Prediction of the acute toxicity (96-h LC50) of organic compounds to the fathead minnow (Pimephales promelas) using a group contribution method.

T M Martin1, D M Young.   

Abstract

A group contribution method has been developed to correlate the acute toxicity (96-h LC50) to the fathead minnow (Pimephales promelas) for 397 organic chemicals. Multilinear regression and computational neural networks (CNNs) were used for model building. The models were able to achieve a fairly good correlation of the data (r2 > 0.9). The linear model, which included four specific interaction terms, provided a rapid means of predicting the toxicity of a compound. The CNN model was able to yield virtually the same predictions with or without the four interaction terms that were included in the multilinear model.

Entities:  

Mesh:

Substances:

Year:  2001        PMID: 11599929     DOI: 10.1021/tx0155045

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  12 in total

1.  QSAR model for predicting the toxicity of organic compounds to fathead minnow.

Authors:  Qingzhu Jia; Yunpeng Zhao; Fangyou Yan; Qiang Wang
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-22       Impact factor: 4.223

2.  Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Lethal Concentrations and Points of Departure.

Authors:  Thomas Y Sheffield; Richard S Judson
Journal:  Environ Sci Technol       Date:  2019-10-10       Impact factor: 9.028

3.  KRAKENX: software for the generation of alignment-independent 3D descriptors.

Authors:  Vishwesh Venkatraman; Bjørn Kåre Alsberg
Journal:  J Mol Model       Date:  2016-03-29       Impact factor: 1.810

4.  Demonstration of a consensus approach for the calculation of physicochemical properties required for environmental fate assessments.

Authors:  Caroline Tebes-Stevens; Jay M Patel; Michaela Koopmans; John Olmstead; Said H Hilal; Nick Pope; Eric J Weber; Kurt Wolfe
Journal:  Chemosphere       Date:  2017-11-23       Impact factor: 7.086

5.  Alterations of larval photo-dependent swimming responses (PDR): New endpoints for rapid and diagnostic screening of aquatic contamination.

Authors:  Luis Colón-Cruz; Lauren Kristofco; Jonathan Crooke-Rosado; Agnes Acevedo; Aranza Torrado; Bryan W Brooks; María A Sosa; Martine Behra
Journal:  Ecotoxicol Environ Saf       Date:  2017-09-19       Impact factor: 6.291

6.  Direct Prediction of Physicochemical Properties and Toxicities of Chemicals from Analytical Descriptors by GC-MS.

Authors:  Yasuyuki Zushi
Journal:  Anal Chem       Date:  2022-06-14       Impact factor: 8.008

7.  Framework towards more Sustainable Chemical Synthesis Design - A Case Study of Organophosphates.

Authors:  Michael A Gonzalez; Sudhakar Takkellapati; Kidus Tadele; Tao Li; Rajender S Varma
Journal:  ACS Sustain Chem Eng       Date:  2019-02-25       Impact factor: 8.198

8.  Accelerating the pace of ecotoxicological assessment using artificial intelligence.

Authors:  Runsheng Song; Dingsheng Li; Alexander Chang; Mengya Tao; Yuwei Qin; Arturo A Keller; Sangwon Suh
Journal:  Ambio       Date:  2021-08-24       Impact factor: 6.943

9.  Corrosion Inhibition of Mild Steel in Hydrochloric Acid Environments Containing Sonneratia caseolaris Leaf Extract.

Authors:  Tran Dinh Manh; Thanh Liem Huynh; Bui Viet Thi; Sunhwa Lee; Junsin Yi; Nam Nguyen Dang
Journal:  ACS Omega       Date:  2022-03-01

10.  Defining the Human-Biota Thresholds of Toxicological Concern for Organic Chemicals in Freshwater: The Proposed Strategy of the LIFE VERMEER Project Using VEGA Tools.

Authors:  Diego Baderna; Roberta Faoro; Gianluca Selvestrel; Adrien Troise; Davide Luciani; Sandrine Andres; Emilio Benfenati
Journal:  Molecules       Date:  2021-03-30       Impact factor: 4.411

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.