Literature DB >> 18261511

Application of the modelling power approach to variable subset selection for GA-PLS QSAR models.

Salvador Sagrado1, Mark T D Cronin.   

Abstract

A previously developed function, the Modelling Power Plot, has been applied to QSARs developed using partial least squares (PLS) following variable selection from a genetic algorithm (GA). Modelling power (Mp) integrates the predictive and descriptive capabilities of a QSAR. With regard to QSARs for narcotic toxic potency, Mp was able to guide the optimal selection of variables using a GA. The results emphasise the importance of Mp to assess the success of the variable selection and that techniques such as PLS are more robust following variable selection.

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Year:  2008        PMID: 18261511     DOI: 10.1016/j.aca.2008.01.013

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  5 in total

1.  Chemometrics analysis for investigation of retention behavior of hazardous compounds in effluents.

Authors:  Hamzeh Karimi; Abbas Farmany; Hadi Noorizadeh
Journal:  Environ Monit Assess       Date:  2012-03-08       Impact factor: 2.513

2.  In silico evaluation, molecular docking and QSAR analysis of quinazoline-based EGFR-T790M inhibitors.

Authors:  M Asadollahi-Baboli
Journal:  Mol Divers       Date:  2016-05-21       Impact factor: 2.943

3.  A quantitative structure- property relationship of gas chromatographic/mass spectrometric retention data of 85 volatile organic compounds as air pollutant materials by multivariate methods.

Authors:  Maryam Sarkhosh; Jahan B Ghasemi; Mahnaz Ayati
Journal:  Chem Cent J       Date:  2012-05-02       Impact factor: 4.215

4.  A Comparative QSAR Analysis, Molecular Docking and PLIF Studies of Some N-arylphenyl-2, 2-Dichloroacetamide Analogues as Anticancer Agents.

Authors:  Masood Fereidoonnezhad; Zeinab Faghih; Ayyub Mojaddami; Zahra Rezaei; Amirhossein Sakhteman
Journal:  Iran J Pharm Res       Date:  2017       Impact factor: 1.696

5.  QSAR models for CXCR2 receptor antagonists based on the genetic algorithm for data preprocessing prior to application of the PLS linear regression method and design of the new compounds using in silico virtual screening.

Authors:  Tahereh Asadollahi; Shayessteh Dadfarnia; Ali Mohammad Haji Shabani; Jahan B Ghasemi; Maryam Sarkhosh
Journal:  Molecules       Date:  2011-02-25       Impact factor: 4.411

  5 in total

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