Applications D′Intelligence Artificielle Dans La Chimie Organique. XVII. Nouveaux Programmes Du Projet SISTEMAT

Emerenciano, Vincente de Paulo; Rodrigues, Gilberto do Vale; Macari, P. A. T.; Vesti, S. A.; Borges, Joao H. G.; Gastmans, J. P.; Fromanteau, Denise L. G.

doi:10.1155/1994/702697

Cited by 23 publications

(14 citation statements)

References 3 publications

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“…The former task has been thoroughly explored by our research group. [4][5][6][7][8][9][10][11][12][13][14][15][16] The latter is only beginning. 17 The system allows the analysis of the The database of SISTEMAT shows all the facilities of an associated database allied to the storage of compound structures in compacted vector forms, which are transformed into connectivity matrices during the search process.…”

Section: Methodsmentioning

confidence: 99%

“…[1][2][3][4][5][6][7][8][9][10][11] Substructures, allied to other biochemical inferences, are the main tools for chemotaxonomy methodology, and may be useful to discrimimate genera, species etc. 12,13 The aim of this work is to demonstrate how a specialist system developed to assist the chemist in both fields described above can be used for chemotaxonomic purposes.…”

Section: Introductionmentioning

confidence: 99%

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SISTAX: an intelligent tool for recovering information on natural products chemistry

Alvarenga

Gastmans

Ferreira

et al. 2003

J. Braz. Chem. Soc.

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Este trabalho descreve o desenvolvimento de um novo programa para o sistema especialista SISTEMAT, denominado de SISTAX. Este programa permite aos interessados em quimiotaxonomia realizar uma "pesquisa inteligente" de substâncias orgânicas em bancos de dados através de estruturas químicas. Quando acoplado com um eficiente sistema de códigos, este programa reconhece tipos de esqueletos e pode encontrar quaisquer restrições subestruturais solicitadas pelo usuário. Um exemplo da aplicação do programa para diterpenos encontrados em plantas é descrito.This work describes the development of a new program, named SISTAX, for the expert system SISTEMAT. This program allows anyone interested in chemotaxonomy to carry out an intelligent search for organic compounds in databases through chemical structures. When coupled with can efficient encoding system, the program recognizes skeletal types and can find any substructural constraints demanded by the user. An example of an application of the program to the diterpene class found in plants is described.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

SISTAX: an intelligent tool for recovering information on natural products chemistry

Alvarenga

Gastmans

Ferreira

et al. 2003

J. Braz. Chem. Soc.

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“…In the last couple of years, our research group has developed the SISTEMAT expert system (13,14), whose objective is to aid natural product researchers in the structural determination process of organic substances. For that, the SISTEMAT system utilizes, principally, 13 C NMR, mass spectrometry (MS), and systematic information (family, genus, and species) data.…”

Section: Introductionmentioning

confidence: 99%

“…For that, the SISTEMAT system utilizes, principally, 13 C NMR, mass spectrometry (MS), and systematic information (family, genus, and species) data. Thus, some natural product classes have been studied by us, for example, sesquiterpenes, sesquiterpene lactones, diterpenes, and triterpenes (15)(16)(17)(18)(19), by using the programs of the SISTEMAT, to construct, at the end of the work, a system for elucidation of any terpenoid structure.…”

Section: Introductionmentioning

confidence: 99%

MONOREG an expert system for structural elucidation of monoterpenes

Ferreira¹,

Rodrigues²,

Emerenciano³

2001

Can. J. Chem.

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This paper describes a new expert system denominated MONOREG for structural determination of monoterpenes. This system is composed of five programs capable of performing 13 C NMR spectra data analyses and analyses of systematic data from living organisms. At the end of this procedure, it shows the likely skeletons of the compound in question as well as the substructures compatible with the 13 C NMR data. The system was tested on the skeleton elucidation of 40 monoterpenes from a wide variety of structure types and exhibited excellent results in the skeleton prediction process.Résumé : Cet article décrit un nouveau système expert, dénommé MONOREG, utilisé pour la détermination structurale des monoterpènes. Ce système se compose de cinq programmes qui réalisent l'analyse RMN du 13 C d'un composé et utilize aussi des données de systématiques d'organismes vivants. Les squelettes probables sont déterminés ainsi que les sous-structures compatibles avec les données spectrales. Le système a été testé pour l'élucidation de 40 monoterpènes qui appartiennent à divers types de squelettes, et montre d'excellents résultats.Mots clés : monoterpènes, RMN du 13 C, élucidation structurale, analyse assisteé par ordinateur, système expert. Ferreira et al. 1925The MONOREG system MONOREG is a system that performs data analyses of monoterpenes. The idea for this name comes from the Portuguese words monoterpenos (Engl., monoterpenes) and regras (Engl. rules). Basically, this system is composed of five programs: MACRONO, SISCONST, C13MACH, SISOCBOT, Can. ). and REGRAS, which propose, at the end of analysis, a probable skeleton compatible with the entered data. This system is also capable of carrying out analyses of data from MS, however, these data were not inserted in the system. Therefore, they were not evaluated. The programs mentioned above are described below. The MACRONO programThe MACRONO program (22, 23) identifies the common substituent groups present in the natural products, such as acetate, angelate, tiglate. From the 13 C NMR chemical shifts and respective multiplicities of the substance in question, the program searches the database for the most probable substituent groups present in this substance and shows to the user the selected substituent groups together with their average error range of chemical shifts. The average error range is the average deviation calculated from the chemical shifts of the sample in question and then matched with the chemical shifts values stored in the database. Therefore, the smaller the range, the more reliable the result be will.The database especially elaborated for this program contains 161 substituent groups that are frequently encountered in terpenoid compounds. It is essential that the MACRONO program is the first program to be used in the MONOREG

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“…Data Source. Some of the chemical data were extracted from the database of the expert system SISTEMAT [57], monoterpenes from [38 ± 40] [58], sesquiterpenes from [59], sesquiterpene lactones from [14] [60], diterpenes from [61] [62], triterpenes from [37], coumarins from [63], polyacetylenes from [64], and benzofurans from [65]. These data included works published up to the year 2000.…”

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confidence: 99%

Neural Networks in Chemosystematic Studies of Asteraceae: A Classification Based on a Dichotomic Approach

Ferreira

Brant

Alvarenga

et al. 2005

C&B

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This paper describes the application of artificial neural nets as an alternative and efficient method for the classification of botanical taxa based on chemical data (chemosystematics). A total of 28,000 botanical occurrences of chemical compounds isolated from the Asteraceae family were chosen from the literature, and grouped by chemical class for each species. Four tests were carried out to differentiate and classify different botanical taxa. The qualifying capacity of the artificial neural nets was dichotomically tested at different hierarchical levels of the family, such as subfamilies and groups of Heliantheae subtribes. Furthermore, two specific subtribes of the Heliantheae and two genera of one of these subtribes were also tested. In general, the artificial neural net gave rise to good results, with multiple-correlation values R>0.90. Hence, it was possible to differentiate the dichotomic character of the botanical taxa studied.

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Applications D′Intelligence Artificielle Dans La Chimie Organique. XVII. Nouveaux Programmes Du Projet SISTEMAT

Cited by 23 publications

References 3 publications

SISTAX: an intelligent tool for recovering information on natural products chemistry

SISTAX: an intelligent tool for recovering information on natural products chemistry

MONOREG an expert system for structural elucidation of monoterpenes

Neural Networks in Chemosystematic Studies of Asteraceae: A Classification Based on a Dichotomic Approach

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Applications D′Intelligence Artificielle Dans La Chimie Organique. XVII. Nouveaux Programmes Du Projet SISTEMAT

Cited by 23 publications

References 3 publications

SISTAX: an intelligent tool for recovering information on natural products chemistry

SISTAX: an intelligent tool for recovering information on natural products chemistry

MONOREG  an expert system for structural elucidation of monoterpenes

Neural Networks in Chemosystematic Studies of Asteraceae: A Classification Based on a Dichotomic Approach

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MONOREG an expert system for structural elucidation of monoterpenes