QSPR Study of the Distribution Coefficient Property for Hydantoin and 5-Arylidene Derivatives. A Genetic Algorithm Application for the Variable Selection in the MLR and PLS Methods-Reference-Cited by-同舟云学术

QSPR Study of the Distribution Coefficient Property for Hydantoin and 5-Arylidene Derivatives. A Genetic Algorithm Application for the Variable Selection in the MLR and PLS Methods

Published:2008-10 Issue:5 Volume:55 Page:1086-1093
ISSN:0009-4536
Container-title:Journal of the Chinese Chemical Society
language:en
Short-container-title:Jnl Chinese Chemical Soc

Author:

Riahi Siavash,Pourbasheer Eslam,Ganjali Mohammad Reza,Norouzi Parviz,Moghaddam Ali Zeraatkar

Publisher

Wiley

Subject

General Chemistry

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/jccs.200800159/fullpdf

Reference48 articles.

1. Chapter 17. Recent Advances in the Chemistry and Biology of Anti-mycobacterial Agents

2. Treatment and Prophylaxis of Disseminated Mycobacterium Avium Complex in HIV-Infected Individuals

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A comprehensive evaluation of liposome/water partition coefficient prediction models based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method: Challenges from different descriptor dimension reduction methods and machine learning algorithms;Journal of Hazardous Materials;2023-02

2. High Accurate Prediction of Carbonate Selectivity of PVC-Plasticized Membranes Sensors by Genetic Algorithm-Support Vector Machine;ANAL BIOANAL ELECTRO;2023

3. Versatile modelling of polyoxymethylene-water partition coefficients for hydrophobic organic contaminants using linear and nonlinear approaches;Science of The Total Environment;2020-08

4. Prediction of some thermodynamic properties of sulfonamide drugs using genetic algorithm‐multiple linear regressions;Journal of the Chinese Chemical Society;2019-09-16

5. Prediction of PCE of fullerene (C 60 ) derivatives as polymer solar cell acceptors by genetic algorithm–multiple linear regression;Journal of Industrial and Engineering Chemistry;2015-01