MARC表示: Biological data integration and web services composition using semantic web and artificial intelligence planning

Biological data integration and web services composition using semantic web and artificial intelligence planning

Systems biology research relies on data integration and retrieval which are performed during the early stages of biological research to enable biologists to understand a wide range of biological data including gene and pathway. In data retrieval, web services are utilized to retrieve integrated data...

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第一著者:	Remli, Muhammad Akmal
フォーマット:	学位論文
出版事項:	2014
主題:	TK Electrical engineering. Electronics Nuclear engineering
オンライン･アクセス:	http://eprints.utm.my/id/eprint/41599/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:78203?queryType=vitalDismax&query=Biological+data+integration+and+web+services&public=true
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id	my.utm.41599
record_format	eprints
spelling	my.utm.415992017-06-14T06:01:34Z http://eprints.utm.my/id/eprint/41599/ Biological data integration and web services composition using semantic web and artificial intelligence planning Remli, Muhammad Akmal TK Electrical engineering. Electronics Nuclear engineering Systems biology research relies on data integration and retrieval which are performed during the early stages of biological research to enable biologists to understand a wide range of biological data including gene and pathway. In data retrieval, web services are utilized to retrieve integrated data from a repository using web service composition. This service composition would combine multiple services whenever some requirements cannot be fulfilled by a single service. In web service composition, many of the planning algorithms to detect and generate composition plan would focus only on sequence composition thus, neglecting concurrent composition. Besides that, data integration methods cater to biological data which are heterogeneous and these methods focus on general data without taking into consideration specific bacterium data. The research is aimed at developing data integration and retrieval approach using semantic web and web service composition. In this approach, a semantic web and transformation method was applied to integrate protein, gene and pathway data of specific bacterium (Lactococcus Lactis) from several resources. The integrated data are expressed in Resource Description Framework (RDF) format and published in RDF repository. In the web service composition, Artificial Intelligence (AI) planning algorithm was developed to automate the composition by depicting the problem as an AI planning problem. The proposed planning algorithms extended the Hierarchical Task Network (HTN) in the context of concurrent service composition. The approach produced integrated results which were evaluated in terms of connected instances of biological data by performing query over RDF repository. Experimental analysis of service composition showed that the proposed algorithms are capable of detecting and generating concurrent plan when compared with existing algorithms. The research has extended data integration and retrieval approaches by combining them using a semantic web presented in RDF format as well as illustrated that the proposed algorithms can be applied effectively for data retrieval in the context of concurrent web service composition 2014 Thesis NonPeerReviewed Remli, Muhammad Akmal (2014) Biological data integration and web services composition using semantic web and artificial intelligence planning. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computing. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:78203?queryType=vitalDismax&query=Biological+data+integration+and+web+services&public=true
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Remli, Muhammad Akmal Biological data integration and web services composition using semantic web and artificial intelligence planning
description	Systems biology research relies on data integration and retrieval which are performed during the early stages of biological research to enable biologists to understand a wide range of biological data including gene and pathway. In data retrieval, web services are utilized to retrieve integrated data from a repository using web service composition. This service composition would combine multiple services whenever some requirements cannot be fulfilled by a single service. In web service composition, many of the planning algorithms to detect and generate composition plan would focus only on sequence composition thus, neglecting concurrent composition. Besides that, data integration methods cater to biological data which are heterogeneous and these methods focus on general data without taking into consideration specific bacterium data. The research is aimed at developing data integration and retrieval approach using semantic web and web service composition. In this approach, a semantic web and transformation method was applied to integrate protein, gene and pathway data of specific bacterium (Lactococcus Lactis) from several resources. The integrated data are expressed in Resource Description Framework (RDF) format and published in RDF repository. In the web service composition, Artificial Intelligence (AI) planning algorithm was developed to automate the composition by depicting the problem as an AI planning problem. The proposed planning algorithms extended the Hierarchical Task Network (HTN) in the context of concurrent service composition. The approach produced integrated results which were evaluated in terms of connected instances of biological data by performing query over RDF repository. Experimental analysis of service composition showed that the proposed algorithms are capable of detecting and generating concurrent plan when compared with existing algorithms. The research has extended data integration and retrieval approaches by combining them using a semantic web presented in RDF format as well as illustrated that the proposed algorithms can be applied effectively for data retrieval in the context of concurrent web service composition
format	Thesis
author	Remli, Muhammad Akmal
author_facet	Remli, Muhammad Akmal
author_sort	Remli, Muhammad Akmal
title	Biological data integration and web services composition using semantic web and artificial intelligence planning
title_short	Biological data integration and web services composition using semantic web and artificial intelligence planning
title_full	Biological data integration and web services composition using semantic web and artificial intelligence planning
title_fullStr	Biological data integration and web services composition using semantic web and artificial intelligence planning
title_full_unstemmed	Biological data integration and web services composition using semantic web and artificial intelligence planning
title_sort	biological data integration and web services composition using semantic web and artificial intelligence planning
publishDate	2014
url	http://eprints.utm.my/id/eprint/41599/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:78203?queryType=vitalDismax&query=Biological+data+integration+and+web+services&public=true
_version_	1643650663753711616
score	13.250246

Biological data integration and web services composition using semantic web and artificial intelligence planning

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