Comparative Study of QSAR/QSPR Correlations Using Support Vector Machines, Radial Basis Function Neural Networks, and Multiple Linear Regression-Reference-Cited by-全球学者库

Comparative Study of QSAR/QSPR Correlations Using Support Vector Machines, Radial Basis Function Neural Networks, and Multiple Linear Regression

Published:2004-04-23 Issue:4 Volume:44 Page:1257-1266
ISSN:0095-2338
Container-title:Journal of Chemical Information and Computer Sciences
language:en
Short-container-title:J. Chem. Inf. Comput. Sci.

Author:

Yao X. J.¹,Panaye A.¹,Doucet J. P.¹,Zhang R. S.¹,Chen H. F.¹,Liu M. C.¹,Hu Z. D.¹,Fan B. T.¹

Affiliation:

1. Université Paris 7-Denis Diderot, ITODYS-CNRS UMR 7086, 1, Rue Guy de la Brosse, 75005 Paris, France, and Department of Chemistry, Lanzhou University, Lanzhou 730000, China

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/ci049965i

Reference33 articles.

1. The Present Utility and Future Potential for Medicinal Chemistry of QSAR / QSPR with Whole Molecule Descriptors

2. Handbook of Molecular Descriptors

3. Topological Indices and Related Descriptors in QSAR and QSPR; Devillers, J., Balaban, A. T., Eds.; Gordon and Breach: Amsterdam, The Netherlands, 1999.

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