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Towards semantic systems biology: biological knowledge management using semantic web technologies

Erick Zimar Antezana San Roman UGent (2009)
abstract
New knowledge is produced at a continuously increasing speed, and the list of papers, databases and other knowledge sources that a researcher in the life sciences needs to cope with is actually turning into a problem rather than an asset. The adequate management of knowledge is therefore becoming fundamentally important for life scientists, especially if they work with approaches that thoroughly depend on knowledge integration, such as Systems Biology. Several initiatives to organise biological knowledge sources into a readily exploitable resource are currently being carried out. Ontologies and Semantic Web technologies revolutionise these efforts. In this thesis, the benefits, current possibilities and the potential of these technologies for the biosciences are reported. This study has three major products, which are comprehensively introduced and discussed: ONTO-PERL, the Cell Cycle Ontology and BioGateway. ONTO-PERL is presented as an OBO-centered PERL API that provides a turnkey service to help bio-ontologists handle ontologies, do data exploration, and perform data mining. The Cell Cycle Ontology is an application ontology that automatically captures and integrates detailed knowledge of the cell cycle process by interlinking knowledge from various sources. CCO uses Semantic Web technologies, and it is accessible via the web for browsing, visualising, advanced querying, and computational reasoning. CCO facilitates a detailed analysis of cell cycle related molecular network components. Through querying and automated reasoning it may support Systems Biology approaches to biological network building. Also, a semantically integrated resource named BioGateway is presented. BioGateway comprises the entire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROT protein set, the NCBI taxonomy and several in-house developed ontologies. BioGateway provides a single entry point to query these resources through the SPARQL query language. The concept of Semantic Systems Biology is introduced as an approach complementary to mathematical model-based Systems Biology which might pave the way towards the construction of a universal, interoperable biological knowledge architecture. BioGateway constitutes a key component for a Semantic Systems Biology approach to generate new hypotheses concerning systems properties. Finally, the trends that the Semantic Web technologies hold for the management of biological knowledge are discussed.
Please use this url to cite or link to this publication:
author
promoter
UGent and Martin Kuiper
organization
year
type
dissertation (composite)
subject
keyword
Open Biomedical Ontologies, data integration, OBO, Web Ontology Language, OWL, Resource Description Framework, RDF, triple store, standarisation, knowledge representation, knowledge management, semantic systems biology, systems biology, reasoning, cell cycle, biogateway, terminologies, terminology, semantics, WWW, semantic web, bioinformatics, bio-ontologies, ontology, ontologies
pages
192 in multiple pagination pages
publisher
Ghent University. Faculty of Sciences
place of publication
Ghent, Belgium
defense location
Zwijnaarde : Fiers-Schell_Van Montagu building (Seminarieruimte)
defense date
2009-09-28 16:00
language
English
UGent publication?
yes
classification
D1
copyright statement
I have retained and own the full copyright for this publication
id
764729
handle
http://hdl.handle.net/1854/LU-764729
alternative location
http://lib.ugent.be/fulltxt/RUG01/001/355/727/RUG01-001355727_2010_0001_AC.pdf
date created
2009-10-19 10:25:30
date last changed
2009-10-21 14:11:21
@phdthesis{764729,
  abstract     = {New knowledge is produced at a continuously increasing speed, and the list of papers, databases and other knowledge sources that a researcher in the life sciences needs to cope with is actually turning into a problem rather than an asset. The adequate management of knowledge is therefore becoming fundamentally important for life scientists, especially if they work with approaches that thoroughly depend on knowledge integration, such as Systems Biology. 

Several initiatives to organise biological knowledge sources into a  readily exploitable resource are currently being carried out. Ontologies and Semantic Web technologies revolutionise these efforts. In this  thesis, the benefits, current possibilities and the potential of these technologies for the biosciences are reported. 

This study has three major products, which are comprehensively introduced and discussed: ONTO-PERL, the Cell Cycle Ontology and BioGateway. ONTO-PERL is presented as an OBO-centered PERL API that provides a turnkey service to help bio-ontologists handle ontologies, do data exploration, and perform data mining. The Cell Cycle Ontology is an application ontology that automatically captures and integrates detailed knowledge of the cell cycle process by interlinking knowledge from various sources. CCO uses Semantic Web technologies, and it is accessible via the web for browsing, visualising, advanced querying, and computational reasoning. CCO facilitates a detailed analysis of cell cycle related molecular network components. Through querying and automated reasoning it may support Systems Biology approaches to biological network building. Also, a semantically integrated resource named BioGateway is presented. BioGateway comprises the entire set of the OBO foundry candidate ontologies, the GO annotation files, the SWISS-PROT protein set, the NCBI taxonomy and several in-house developed ontologies. BioGateway provides a single entry point to query these resources through the SPARQL query language. 

The concept of Semantic Systems Biology is introduced as an approach complementary to mathematical model-based Systems Biology which might pave the way towards the construction of a universal, interoperable biological knowledge architecture. BioGateway constitutes a key component for a Semantic Systems Biology approach to generate new hypotheses concerning systems properties. Finally, the trends that the Semantic Web technologies hold for the management of biological knowledge are discussed.},
  author       = {Antezana San Roman, Erick Zimar},
  keyword      = {Open Biomedical Ontologies,data integration,OBO,Web Ontology Language,OWL,Resource Description Framework,RDF,triple store,standarisation,knowledge representation,knowledge management,semantic systems biology,systems biology,reasoning,cell cycle,biogateway,terminologies,terminology,semantics,WWW,semantic web,bioinformatics,bio-ontologies,ontology,ontologies},
  language     = {eng},
  pages        = {192 in multiple pagination},
  publisher    = {Ghent University. Faculty of Sciences},
  school       = {Ghent University},
  title        = {Towards semantic systems biology: biological knowledge management using semantic web technologies},
  url          = {http://lib.ugent.be/fulltxt/RUG01/001/355/727/RUG01-001355727\_2010\_0001\_AC.pdf},
  year         = {2009},
}

Chicago
Antezana San Roman, Erick Zimar. 2009. “Towards Semantic Systems Biology: Biological Knowledge Management Using Semantic Web Technologies”. Ghent, Belgium: Ghent University. Faculty of Sciences.
APA
Antezana San Roman, E. Z. (2009). Towards semantic systems biology: biological knowledge management using semantic web technologies. Ghent University. Faculty of Sciences, Ghent, Belgium.
Vancouver
1.
Antezana San Roman EZ. Towards semantic systems biology: biological knowledge management using semantic web technologies. [Ghent, Belgium]: Ghent University. Faculty of Sciences; 2009.
MLA
Antezana San Roman, Erick Zimar. “Towards Semantic Systems Biology: Biological Knowledge Management Using Semantic Web Technologies.” 2009 : n. pag. Print.