期刊
BIOINFORMATICS
卷 27, 期 3, 页码 405-407出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btq680
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资金
- OTKA [CNK 77780]
- NKTH
- EU [TAMOP 4.2.1./B-09/1/KMR-2010-0003]
Motivation: Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Results: Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients.
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