Application of Cascade Correlation Networks for Structures to Chemistry
 Anna Maria Bianucci,
 Alessio Micheli,
 Alessandro Sperduti,
 Antonina Starita
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We present the application of Cascade Correlation for structures to QSPR (quantitative structureproperty relationships) and QSAR (quantitative structureactivity relationships) analysis. Cascade Correlation for structures is a neural network model recently proposed for the processing of structured data. This allows the direct treatment of chemical compounds as labeled trees, which constitutes a novel approach to QSPR/QSAR. We report the results obtained for QSPR on Alkanes (predicting the boiling point) and QSAR of a class of Benzodiazepines. Our approach compares favorably versus the traditional QSAR treatment based on equations and it is competitive with ‘ad hoc’ MLPs for the QSPR problem.
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 Title
 Application of Cascade Correlation Networks for Structures to Chemistry
 Journal

Applied Intelligence
Volume 12, Issue 12 , pp 117147
 Cover Date
 20000101
 DOI
 10.1023/A:1008368105614
 Print ISSN
 0924669X
 Online ISSN
 15737497
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 Cascade Correlation networks
 constructive algorithms
 gradient descent
 QSPR
 QSAR
 Industry Sectors
 Authors

 Anna Maria Bianucci ^{(1)}
 Alessio Micheli ^{(2)}
 Alessandro Sperduti ^{(2)}
 Antonina Starita ^{(2)}
 Author Affiliations

 1. Dipartimento di Scienze Farmaceutiche, Via Bonanno 6, 56126, Pisa, Italy
 2. Dipartimento di Informatica, Università di Pisa, Corso Italia, 40, 56125, Pisa, Italy