Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/102322
Type: Artigo de periódico
Title: Pattern Recognition And Neural Networks Applied To Structure-activity Relationships Of Neolignans Tested Against Leishmania Amazonensis Using Quantum Chemical And Topological Descriptors
Author: Costa M.C.A.
Barata L.E.S.
Rossi-Bergmann B.
Takahata Y.
Abstract: Pattern recognition (PR) and neural networks (NN) were applied to structure-activity relationship studies of a series of neolignans tested against Leishmania amazonensis. Comparison of NN with PR methods revealed that the capability of the two methods are similar to classify the molecules in the different categories, but it was found that K-nearest neighbors and NN are superior to SIMCA in the activity prevision of a new set of compounds. The applicability of these methods using quantum chemical descriptors and topological indices were investigated.
Editor: 
Rights: fechado
Identifier DOI: 10.1002/qua.10698
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0142007961&partnerID=40&md5=155287594c1974ca16f99bc047e06a13
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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