Literature DB >> 16045297

Modified ant colony optimization algorithm for variable selection in QSAR modeling: QSAR studies of cyclooxygenase inhibitors.

Qi Shen1, Jian-Hui Jiang, Jing-Chao Tao, Guo-Li Shen, Ru-Qin Yu.   

Abstract

A new version of an ant colony optimization (ACO) algorithm has been proposed. A modified ACO algorithm is proposed to select variables in QSAR modeling and to predict inhibiting action of some diarylimidazole derivatives on cyclooxygenase (COX) enzyme. As a comparison to this method, the evolution algorithm (EA) was also tested. Experimental results have demonstrated that the modified ACO is a useful tool for variable selection that needs few parameters to be adjusted and converges quickly toward the optimal position.

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Year:  2005        PMID: 16045297     DOI: 10.1021/ci049610z

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  5 in total

1.  Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

Authors:  Habib MotieGhader; Sajjad Gharaghani; Yosef Masoudi-Sobhanzadeh; Ali Masoudi-Nejad
Journal:  Iran J Pharm Res       Date:  2017       Impact factor: 1.696

2.  A QSAR study of environmental estrogens based on a novel variable selection method.

Authors:  Zhongsheng Yi; Aiqian Zhang
Journal:  Molecules       Date:  2012-05-21       Impact factor: 4.411

3.  A joint optimization QSAR model of fathead minnow acute toxicity based on a radial basis function neural network and its consensus modeling.

Authors:  Yukun Wang; Xuebo Chen
Journal:  RSC Adv       Date:  2020-06-04       Impact factor: 4.036

4.  Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

Authors:  Noel M O'Boyle; David S Palmer; Florian Nigsch; John Bo Mitchell
Journal:  Chem Cent J       Date:  2008-10-29       Impact factor: 4.215

5.  Analytical development and optimization of a graphene-solution interface capacitance model.

Authors:  Hediyeh Karimi; Rasoul Rahmani; Reza Mashayekhi; Leyla Ranjbari; Amir H Shirdel; Niloofar Haghighian; Parisa Movahedi; Moein Hadiyan; Razali Ismail
Journal:  Beilstein J Nanotechnol       Date:  2014-05-09       Impact factor: 3.649

  5 in total

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