Semantic web for integrated network analysis in biomedicine

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Reference:

1. Huajun Chen, Li Ding, Zhaohui Wu, Tong Yu, Lavanya Dhanapalan, Jake Y. Chen. Semantic Web for Integrated Network Analysis in Biomedicine , Briefings in Bioinformatics Advance 10 (2) pp.177-192, 2009

bibtex

@article { chen2009semantic ,
  author = "Huajun Chen, Li Ding, Zhaohui Wu, Tong Yu, Lavanya Dhanapalan, Jake Y. Chen", 
journal = "Briefings in Bioinformatics Advance", 
number = "2", 
pages = "177-192", 
title = "Semantic Web for Integrated Network Analysis in Biomedicine", 
volume = "10", 
year = "2009", 
} 

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.

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• paper: (http://bib.oxfordjournals.org/cgi/content/abstract/10/2/177)
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