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3.
J Chem Inf Comput Sci ; 36(2): 231-8, 1996.
Artigo em Inglês | MEDLINE | ID: mdl-8882810

RESUMO

A neural network which utilized data from the infrared spectra, carbon-13 NMR spectra, and molecular formulas of organic compounds was developed. The network, which had one layer of hidden units, was trained by backpropagation; network parameters were determined by a simplex optimization procedure. A database of 1560 compounds was used for training and testing. The trained network was able to identify with high accuracy the presence of a broad range of substructural features present in the compounds. The number of features identified and the accuracy were significantly greater as compared with networks using data from a single form of spectroscopy. The results have significance for the SESAMI computer-enhanced structure elucidation system.


Assuntos
Redes Neurais de Computação , Análise Espectral/métodos , Computadores , Interpretação Estatística de Dados , Bases de Dados Factuais , Espectroscopia de Ressonância Magnética/métodos , Estrutura Molecular , Espectrofotometria Infravermelho/métodos , Espectrofotometria Infravermelho/estatística & dados numéricos , Análise Espectral/estatística & dados numéricos
4.
J Chem Inf Comput Sci ; 43(5): 1434-46, 2003.
Artigo em Inglês | MEDLINE | ID: mdl-14502476

RESUMO

A new method of structure generation called convergent structure generation has been developed to address limitations of earlier methods. The features of the program (HOUDINI) based on this method include the following: a single integrated representation of the collective substructural information; the use of parallel atom groups for efficient processing of families of alternative substructural inferences; and a managed structure generation procedure designed to build required structural features early in the process.


Assuntos
Compostos Orgânicos/química , Software , Algoritmos , Conformação Molecular , Estrutura Molecular
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