Literature DB >> 14635726

ANVAS: artificial neural variables adaptation system for descriptor selection.

Paolo Mazzatorta1, Marjan Vracko, Emilio Benfenati.   

Abstract

A new algorithm model-oriented for variable selection is presented in this study. It is based on the combination of genetic algorithms (GA) for hyperspace exploration, and counterpropagation artificial neural network (CP ANN) for deriving the fitness score. The proposed method performed very well on both well defined synthetic data sets and real academic data sets.

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Year:  2003        PMID： 14635726     DOI： 10.1023/a:1026132402754

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN： 0920-654X            Impact factor:   3.686


  12 in total

Review 1.  QSAR models for estimating properties of persistent organic pollutants required in evaluation of their environmental fate and risk.

Authors:  A Sabljic
Journal:  Chemosphere       Date:  2001-04       Impact factor: 7.086

2.  Predictive carcinogenicity: a model for aromatic compounds, with nitrogen-containing substituents, based on molecular descriptors using an artificial neural network.

Authors:  G Gini; M Lorenzini; E Benfenati; P Grasso; M Bruschi
Journal:  J Chem Inf Comput Sci       Date:  1999 Nov-Dec

3.  Prediction of mutagenicity utilizing a hierarchical QSAR approach.

Authors:  S C Basak; D Mills
Journal:  SAR QSAR Environ Res       Date:  2001       Impact factor: 3.000

4.  Essential and desirable characteristics of ecotoxicity quantitative structure-activity relationships.

Authors:  T Wayne Schultz; Mark T D Cronin
Journal:  Environ Toxicol Chem       Date:  2003-03       Impact factor: 3.742

5.  Counterpropagation networks.

Authors:  R Hecht-Nielsen
Journal:  Appl Opt       Date:  1987-12-01       Impact factor: 1.980

6.  Outlier detection in multivariate analytical chemical data.

Authors:  W J Egan; S L Morgan
Journal:  Anal Chem       Date:  1998-06-01       Impact factor: 6.986

7.  Neural network studies. 2. Variable selection.

Authors:  I V Tetko; A E Villa; D J Livingstone
Journal:  J Chem Inf Comput Sci       Date:  1996 Jul-Aug

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

Authors:  K Hasegawa; Y Miyashita; K Funatsu
Journal:  J Chem Inf Comput Sci       Date:  1997 Mar-Apr

9.  A QSAR investigation of the role of hydrophobicity in regulating mutagenicity in the Ames test: 1. Mutagenicity of aromatic and heteroaromatic amines in Salmonella typhimurium TA98 and TA100.

Authors:  A K Debnath; G Debnath; A J Shusterman; C Hansch
Journal:  Environ Mol Mutagen       Date:  1992       Impact factor: 3.216

10.  The Carcinogenic Potency Database: analyses of 4000 chronic animal cancer experiments published in the general literature and by the U.S. National Cancer Institute/National Toxicology Program.

Authors:  L S Gold; T H Slone; N B Manley; G B Garfinkel; E S Hudes; L Rohrbach; B N Ames
Journal:  Environ Health Perspect       Date:  1991-12       Impact factor: 9.031
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