Semantic web for integrated network analysis in biomedicine
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| TW-2009-07 | Edit TWTR | |
Citation: Huajun Chen,Li Ding,Zhaohui Wu,Tong Yu,Lavanya Dhanapalan,Jake Y. Chen. (2009) Semantic Web for Integrated Network Analysis in Biomedicine. In Briefings in Bioinformatics Advance, 10,2,177-192,2009.
| Publication article ( Edit ) | |
| type | Journal Paper |
| bibtype | article |
| Bibtex basics | |
| author | Huajun Chen;Li Ding;Zhaohui Wu;Tong Yu;Lavanya Dhanapalan;Jake Y. Chen |
| title | Semantic Web for Integrated Network Analysis in Biomedicine |
| journal | Briefings in Bioinformatics Advance |
| volume | 10 |
| number | 2 |
| pages | 177-192 |
| year | 2009 |
| Bibtex more | |
| Access Paper | |
| 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. |
| paper url | http://bib.oxfordjournals.org/cgi/content/abstract/10/2/177 |
Facts about Semantic web for integrated network analysis in biomedicineRDF feed
| 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 +, and Jake Y. Chen + |
| Bibtype | article + |
| Has author | Huajun Chen +, Li Ding +, Zhaohui Wu +, Tong Yu +, Lavanya Dhanapalan +, and Jake Y. Chen + |
| Has identifier | TW-2009-07 + |
| Has publishing details | 10,2,177-192,2009 + |
| Has title | Semantic Web for Integrated Network Analysis in Biomedicine + |
| Has tr id | TW-2009-07 + |
| Has where published | Briefings in Bioinformatics Advance + |
| Has year | 2009 + |
| Journal | Briefings in Bioinformatics Advance + |
| Number | 2 + |
| Pages | 177-192 + |
| Paper url | http://bib.oxfordjournals.org/cgi/content/abstract/10/2/177 + |
| Title | Semantic Web for Integrated Network Analysis in Biomedicine + |
| Volume | 10 + |
| Year | 2009 + |
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