Literature DB >> 2202830

Neural networks applied to quantitative structure-activity relationship analysis.

T Aoyama1, Y Suzuki, H Ichikawa.   

Abstract

An application of the neural network to quantitative structure-activity relationship (QSAR) analysis has been studied. The new method was compared with the linear multiregression analysis in various ways. It was found that the neural network can be a potential tool in the routine work of QSAR analysis. The mathematical relationship of operation between the neural network and the multiregression analysis was described. It was shown that the neural network can exceed the level of the linear multiregression analysis.

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Year:  1990        PMID: 2202830     DOI: 10.1021/jm00171a037

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  5 in total

1.  Novel approach to evolutionary neural network based descriptor selection and QSAR model development.

Authors:  Zeljko Debeljak; Viktor Marohnić; Goran Srecnik; Marica Medić-Sarić
Journal:  J Comput Aided Mol Des       Date:  2006-04-11       Impact factor: 3.686

2.  Data modelling with neural networks: advantages and limitations.

Authors:  D J Livingstone; D T Manallack; I V Tetko
Journal:  J Comput Aided Mol Des       Date:  1997-03       Impact factor: 3.686

3.  A model-based ensembling approach for developing QSARs.

Authors:  Qianyi Zhang; Jacqueline M Hughes-Oliver; Raymond T Ng
Journal:  J Chem Inf Model       Date:  2009-08       Impact factor: 4.956

Review 4.  Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Authors:  Neetu Tripathi; Manoj Kumar Goshisht; Sanat Kumar Sahu; Charu Arora
Journal:  Mol Divers       Date:  2021-06-10       Impact factor: 2.943

5.  QSAR analysis of pyrimidine derivatives as VEGFR-2 receptor inhibitors to inhibit cancer using multiple linear regression and artificial neural network.

Authors:  Fariba Masoomi Sefiddashti; Saeid Asadpour; Hedayat Haddadi; Shima Ghanavati Nasab
Journal:  Res Pharm Sci       Date:  2021-10-15
  5 in total

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