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Semantic web for integrated network analysis in biomedicine
Abstract The Semantic Web technology enables integr The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis. lysis and herb-drug interactions analysis.
Author Huajun Chen +, Li Ding +, Zhaohui Wu +, Tong Yu +, Lavanya Dhanapalan +, Jake Y. Chen +
Bibtype article  +
Journal Briefings in Bioinformatics Advance +
Key chen2009semantic  +
Modification dateThis property is a special property in this wiki. 2 May 2009 05:15:53  +
Number 2  +
Pages 177-192  +
Paper url http://bib.oxfordjournals.org/cgi/content/abstract/10/2/177  +
Tag Computer science +
Title Semantic Web for Integrated Network Analysis in Biomedicine  +
Tr id TW-2009-07  +
Volume 10 +
Year 2009  +
Categories Journal Paper, Publication, TW Technical Report
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