Toward a Principled Methodology for Neural Network Design and Performance Evaluation in QSAR. Application to the Prediction of LogP-Reference-Cited by-同舟云学术

Toward a Principled Methodology for Neural Network Design and Performance Evaluation in QSAR. Application to the Prediction of LogP

Published:1998-06-04 Issue:4 Volume:38 Page:586-594
ISSN:0095-2338
Container-title:Journal of Chemical Information and Computer Sciences
language:en
Short-container-title:J. Chem. Inf. Comput. Sci.

Author:

Duprat A. F.¹,Huynh T.¹,Dreyfus G.¹

Affiliation:

1. Laboratoire de Recherches Organiques and Laboratoire d'Électronique, École Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75231 Paris Cedex 05, France

Publisher

American Chemical Society (ACS)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci980042v

Reference32 articles.

1. Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives

2. Neural networks prediction of partition coefficients

3. Prediction of Chromatographic Retention Values (RM) and Partition Coefficients (log Poct) Using a Combination of Semiempirical Self-Consistent Reaction Field Calculations and Neural Networks

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