Semantic web for integrated network analysis in biomedicine

被引：32

作者：

Chen, Huajun ^{[1
]}

Ding, Li ^{[2
]}

Wu, Zhaohui ^{[1
]}

Yu, Tong ^{[1
]}

Dhanapalan, Lavanya ^{[3
]}

Chen, Jake Y. ^{[3
,4
]}

机构：

[1] Zhejiang Univ, Sch Comp Sci, Hangzhou, Zhejiang, Peoples R China

[2] Rensselaer Polytech Inst, Tetherless World Constellat, Troy, NY 12181 USA

[3] Purdue Univ, Dept Comp & Informat Sci, W Lafayette, IN 47907 USA

[4] Indiana Univ, Sch Informat, Bloomington, IN 47405 USA

来源：

BRIEFINGS IN BIOINFORMATICS | 2009年 / 10卷 / 02期

基金：

美国国家科学基金会;

关键词：

Semantic Web; network biology; network medicine; graph mining; biomedical network analysis; FUNCTIONAL MODULES; PROTEIN RANKING; DISCOVERY; MOTIFS; IDENTIFICATION; TECHNOLOGIES; ORGANIZATION; METHODOLOGY; MODULARITY; ALGORITHM;

D O I：

10.1093/bib/bbp002

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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 herbdrug interactions analysis.

引用

页码：177 / 192

页数：16

共 80 条

[11] Kernel methods for predicting protein-protein interactions
Ben-Hur, A
Noble, WS
[J]. BIOINFORMATICS, 2005, 21 : I38 - I46
[12] Local graph alignment and motif search in biological networks
Berg, J
Lässig, M
[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 (41) : 14689 - 14694
[13] The Semantic Web - A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities
Berners-Lee, T
Hendler, J
Lassila, O
[J]. SCIENTIFIC AMERICAN, 2001, 284 (05) : 34 - +
[14] BHUVAN B, 2005, P INT WORKSH SEM WEB
[15] CARROLL JJ, 2005, P WORLD WID WEB C
[16] Graph mining: Laws, generators, and algorithms
Chakrabarti, Deepayan
Faloutsos, Christos
[J]. ACM COMPUTING SURVEYS, 2006, 38 (01) : A1 - A69
[17] Chen Jake Y, 2007, J Bioinform Comput Biol, V5, P383, DOI 10.1142/S0219720007002606
[18] CHEN JY, 2009, BMC GENOMIC IN PRESS
[19] Ciriello Giovanni, 2008, Briefings in Functional Genomics & Proteomics, V7, P147, DOI 10.1093/bfgp/eln015
[20] Metabolic PathFinding: inferring relevant pathways in biochemical networks
Croes, D
Couche, F
Wodak, SJ
van Helden, J
[J]. NUCLEIC ACIDS RESEARCH, 2005, 33 : W326 - W330

← 1 2 3 4 5 6 7 8 →