title: Semantic web for integrated network analysis in biomedicine.
abstract: 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.
authors.affiliation: School of Computer Science, Zhejiang University. huajunsir@gmail.com
authors.forename: Huajun
authors.initials: H
authors.lastname: Chen
authors.forename: Li
authors.initials: L
authors.lastname: Ding
authors.forename: Zhaohui
authors.initials: Z
authors.lastname: Wu
authors.forename: Tong
authors.initials: T
authors.lastname: Yu
authors.forename: Lavanya
authors.initials: L
authors.lastname: Dhanapalan
authors.forename: Jake Y
authors.initials: JY
authors.lastname: Chen
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D008490:Medical Informatics / Q000379:methods*; D012660:Semantics; D018511:Systems Integration