Literature DB >> 9157101

GA strategy for variable selection in QSAR studies: GA-based PLS analysis of calcium channel antagonists.

K Hasegawa1, Y Miyashita, K Funatsu.   

Abstract

The GAPLS (GA based PLS) program has been developed for variable selection in QSAR studies. The modified GA was employed to obtain a PLS model with high internal predictivity using a small number of variables. In order to show the performance of GAPLS for variable selection, the program was applied to the inhibitor activity of calcium channel antagonists. As a result, variables largely contributing to the inhibitory activity could be selected, and the structural requirements for the inhibitory activity could be estimated in an effective manner.

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Year:  1997        PMID： 9157101     DOI： 10.1021/ci960047x

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN： 0095-2338


  14 in total

1.  ANVAS: artificial neural variables adaptation system for descriptor selection.

Authors:  Paolo Mazzatorta; Marjan Vracko; Emilio Benfenati
Journal:  J Comput Aided Mol Des       Date:  2003 May-Jun       Impact factor: 3.686

2.  Using particle swarms for the development of QSAR models based on K-nearest neighbor and kernel regression.

Authors:  Walter Cedeño; Dimitris K Agrafiotis
Journal:  J Comput Aided Mol Des       Date:  2003 Feb-Apr       Impact factor: 3.686

3.  The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study.

Authors:  Victor E Kuz'min; Eugene N Muratov; Anatoly G Artemenko; Leonid Gorb; Mohammad Qasim; Jerzy Leszczynski
Journal:  J Comput Aided Mol Des       Date:  2008-04-02       Impact factor: 3.686

4.  QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action.

Authors:  A G Artemenko; E N Muratov; V E Kuz'min; N N Muratov; E V Varlamova; A V Kuz'mina; L G Gorb; A Golius; F C Hill; J Leszczynski; A Tropsha
Journal:  SAR QSAR Environ Res       Date:  2011-06-30       Impact factor: 3.000

5.  Pharmacological activity and membrane interactions of antiarrhythmics: 4D-QSAR/QSPR analysis.

Authors:  C D Klein; A J Hopfinger
Journal:  Pharm Res       Date:  1998-02       Impact factor: 4.200

6.  Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors.

Authors:  Sawsan Abuhamdah; Maha Habash; Mutasem O Taha
Journal:  J Comput Aided Mol Des       Date:  2013-12-12       Impact factor: 3.686

7.  Docking and 3D-QSAR studies of diverse classes of human aromatase (CYP19) inhibitors.

Authors:  Partha Pratim Roy; Kunal Roy
Journal:  J Mol Model       Date:  2010-03-01       Impact factor: 1.810

8.  Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data.

Authors:  Jia Jin; Quan Wang; Guangman Song
Journal:  Photosynth Res       Date:  2021-09-07       Impact factor: 3.573

9.  QSAR analysis of the inhibition of recombinant CYP 3A4 activity by structurally diverse compounds using a genetic algorithm-combined partial least squares method.

Authors:  Suchada Wanchana; Fumiyoshi Yamashita; Mitsuru Hashida
Journal:  Pharm Res       Date:  2003-09       Impact factor: 4.200

10.  Improvement of the Prediction Power of the CoMFA and CoMSIA Models on Histamine H3 Antagonists by Different Variable Selection Methods.

Authors:  Jahan B Ghasemi; Hossein Tavakoli
Journal:  Sci Pharm       Date:  2012-05-24
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