Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/15761

Title: Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils
Authors: Neves, José
Martins, M. Rosário
Candeias, Fátima
Ferreira, Diana
Arantes, Sílvia
Cruz-Morais, Júlio
Gomes, Guida
Macedo, Joaquim
Abelha, António
Vicente, Henrique
Keywords: Artificial Neuronal Networks
Essential Oils
Knowledge Representation and Reasoning
Logic Programming
Schinus molle L
Schinus terebinthifolius raddi
Issue Date: 2015
Publisher: World Academy of Science Engineering and Technology
Citation: Neves, J., Martins, M.R., Candeias, F., Ferreira, D., Arantes, S., Cruz-Morais, J., Gomes, G., Macedo, J., Abelha, A. & Vicente, H., Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils. World Academy of Science, Engineering and Technology, International Science Index 103, International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering, 9 (7): 679–684, 2015.
Abstract: Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.
URI: http://waset.org/publications/10001626/
http://hdl.handle.net/10174/15761
Type: article
Appears in Collections:ICAAM - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
QUI - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
CQE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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