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Applications of artificial intelligence techniques to organic chemistry. Study on sup 13 C NMR of steroids using computer. Aplicacoes de tecnicas de inteligencia artificial em quimica organica. Estudo, por computador, de RMN sup 13 C de esteroides

Journal Article:

Abstract

This work describes the utilization of two groups of programs in searching for characteristic signals of NMR {sup 13}C steroidal compounds. The first group of programs used data bases with the spectral data and a methodology that enables the choice and the search of substructures. The chemical shifts and multiplicities for each specific substructure are used as rules to identify different types and subtypes of steroidal compounds. The second one was built to apply the rules formulated by the first group of programs and to foresee any skeletal based on a spectral analysis. (author).
Authors:
Lins, A P; [1]  Furlan, M; [2]  Gastmans, G P; [3]  Emerenciano, V P [4] 
  1. Instituto Biologico, Sao Paulo, SP (Brazil). Secao de Farmacologia
  2. UNESP, Araraquara, SP (Brazil). Inst. de Quimica
  3. UNESP, Guaratingueta, SP (Brazil). Inst. de Quimica e Fisica
  4. Sao Paulo Univ., SP (Brazil). Inst. de Quimica
Publication Date:
Jan 01, 1991
Product Type:
Journal Article
Reference Number:
AIX-23-024779; EDB-92-050311
Resource Relation:
Journal Name: Anais da Academia Brasileira de Ciencias; (Brazil); Journal Volume: 63:2
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; STEROIDS; CHEMICAL SHIFT; NUCLEAR MAGNETIC RESONANCE; ARTIFICIAL INTELLIGENCE; CARBON 13; COMPUTER CALCULATIONS; COMPUTER CODES; MULTIPLICITY; CARBON ISOTOPES; EVEN-ODD NUCLEI; ISOTOPES; LIGHT NUCLEI; MAGNETIC RESONANCE; NUCLEI; ORGANIC COMPOUNDS; RESONANCE; STABLE ISOTOPES; 400201* - Chemical & Physicochemical Properties
OSTI ID:
5710908
Country of Origin:
Brazil
Language:
Portuguese
Other Identifying Numbers:
Journal ID: ISSN 0001-3765; CODEN: AABCA
Submitting Site:
INIS
Size:
Pages: 141-153
Announcement Date:
Apr 15, 1992

Journal Article:

Citation Formats

Lins, A P, Furlan, M, Gastmans, G P, and Emerenciano, V P. Applications of artificial intelligence techniques to organic chemistry. Study on sup 13 C NMR of steroids using computer. Aplicacoes de tecnicas de inteligencia artificial em quimica organica. Estudo, por computador, de RMN sup 13 C de esteroides. Brazil: N. p., 1991. Web.
Lins, A P, Furlan, M, Gastmans, G P, & Emerenciano, V P. Applications of artificial intelligence techniques to organic chemistry. Study on sup 13 C NMR of steroids using computer. Aplicacoes de tecnicas de inteligencia artificial em quimica organica. Estudo, por computador, de RMN sup 13 C de esteroides. Brazil.
Lins, A P, Furlan, M, Gastmans, G P, and Emerenciano, V P. 1991. "Applications of artificial intelligence techniques to organic chemistry. Study on sup 13 C NMR of steroids using computer. Aplicacoes de tecnicas de inteligencia artificial em quimica organica. Estudo, por computador, de RMN sup 13 C de esteroides." Brazil.
@misc{etde_5710908,
title = {Applications of artificial intelligence techniques to organic chemistry. Study on sup 13 C NMR of steroids using computer. Aplicacoes de tecnicas de inteligencia artificial em quimica organica. Estudo, por computador, de RMN sup 13 C de esteroides}
author = {Lins, A P, Furlan, M, Gastmans, G P, and Emerenciano, V P}
abstractNote = {This work describes the utilization of two groups of programs in searching for characteristic signals of NMR {sup 13}C steroidal compounds. The first group of programs used data bases with the spectral data and a methodology that enables the choice and the search of substructures. The chemical shifts and multiplicities for each specific substructure are used as rules to identify different types and subtypes of steroidal compounds. The second one was built to apply the rules formulated by the first group of programs and to foresee any skeletal based on a spectral analysis. (author).}
journal = {Anais da Academia Brasileira de Ciencias; (Brazil)}
volume = {63:2}
journal type = {AC}
place = {Brazil}
year = {1991}
month = {Jan}
}