An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach
| Main Author: | |
|---|---|
| Publication Date: | 2016 |
| Other Authors: | , , , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10174/19186 |
Summary: | Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process. |
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An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing ApproachSchinus spp.Essential OilsLogic ProgrammingCase Base ReasoningKnowledge Representation and ReasoningSimilarity AnalysisPlants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process.European Council for Modelling and Simulation2016-12-02T11:27:14Z2016-12-022016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/19186http://hdl.handle.net/10174/19186engNeves, J., Martins, M.R., Candeias, F., Arantes, S., Piteira, A. & Vicente, H., An Assessment of Pharmacological Properties of Schinus Essential Oils – A Soft Computing Approach. In T. Claus, F. Herrmann, M. Manitz & O. Rose Eds., Proceedings 30th European Conference on Modelling and Simulation (ECMS 2016), pp. 107–113, European Council for Modelling and Simulation Edition, 2016.7978-0-9932440-2-5http://www.scs-europe.net/dlib/2016/2016-0107.htmQUIjneves@di.uminho.ptmrm@uevora.ptmfbc@uevora.ptsaa@uevora.ptanaisabelanaisabel14@hotmail.comhvicente@uevora.pthttp://www.scs-europe.net/dlib/2016/2016-0107.htmNeves, JoséMartins, M. RosárioCandeias, FátimaArantes, SilviaPiteira, AnaVicente, Henriqueinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T19:07:39Zoai:dspace.uevora.pt:10174/19186Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:11:01.545028Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| title |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| spellingShingle |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach Neves, José Schinus spp. Essential Oils Logic Programming Case Base Reasoning Knowledge Representation and Reasoning Similarity Analysis |
| title_short |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| title_full |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| title_fullStr |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| title_full_unstemmed |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| title_sort |
An Assessment of Pharmacological Properties of Schinus Essential Oils: A Soft Computing Approach |
| author |
Neves, José |
| author_facet |
Neves, José Martins, M. Rosário Candeias, Fátima Arantes, Silvia Piteira, Ana Vicente, Henrique |
| author_role |
author |
| author2 |
Martins, M. Rosário Candeias, Fátima Arantes, Silvia Piteira, Ana Vicente, Henrique |
| author2_role |
author author author author author |
| dc.contributor.author.fl_str_mv |
Neves, José Martins, M. Rosário Candeias, Fátima Arantes, Silvia Piteira, Ana Vicente, Henrique |
| dc.subject.por.fl_str_mv |
Schinus spp. Essential Oils Logic Programming Case Base Reasoning Knowledge Representation and Reasoning Similarity Analysis |
| topic |
Schinus spp. Essential Oils Logic Programming Case Base Reasoning Knowledge Representation and Reasoning Similarity Analysis |
| description |
Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process. |
| publishDate |
2016 |
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2016-12-02T11:27:14Z 2016-12-02 2016-01-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/10174/19186 http://hdl.handle.net/10174/19186 |
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eng |
| language |
eng |
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Neves, J., Martins, M.R., Candeias, F., Arantes, S., Piteira, A. & Vicente, H., An Assessment of Pharmacological Properties of Schinus Essential Oils – A Soft Computing Approach. In T. Claus, F. Herrmann, M. Manitz & O. Rose Eds., Proceedings 30th European Conference on Modelling and Simulation (ECMS 2016), pp. 107–113, European Council for Modelling and Simulation Edition, 2016. 7 978-0-9932440-2-5 http://www.scs-europe.net/dlib/2016/2016-0107.htm QUI jneves@di.uminho.pt mrm@uevora.pt mfbc@uevora.pt saa@uevora.pt anaisabelanaisabel14@hotmail.com hvicente@uevora.pt http://www.scs-europe.net/dlib/2016/2016-0107.htm |
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European Council for Modelling and Simulation |
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European Council for Modelling and Simulation |
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