NDLI: flowNet: Flow-Based Approach for Efficient Analysis of Complex Biological Networks

Content Provider	IEEE Xplore Digital Library
Author	Young-Rae Cho Lei Shi Aidong Zhang
Copyright Year	2009
Abstract	Biological networks having complex connectivity have been widely studied recently. By characterizing their inherent and structural behaviors in a topological perspective, these studies have attempted to discover hidden knowledge in the systems. However, even though various algorithms with graph-theoretical modeling have provided fundamentals in the network analysis, the availability of practical approaches to efficiently handle the complexity has been limited. In this paper, we present a novel flow-based approach, called flowNet, to efficiently analyze large-sized, complex networks. Our approach is based on the functional influence model that quantifies the influence of a biological component on another. We introduce a dynamic flow simulation algorithm to generate a flow pattern which is a unique characteristic for each component. The set of patterns can be used in identifying functional modules (i.e., clustering). The proposed flow simulation algorithm runs very efficiently in sparse networks. Since our approach uses a weighted network as an input, we also discuss supervised and unsupervised weighting schemes for unweighted biological networks. As experimental results in real applications to the yeast protein interaction network, we demonstrate that our approach outperforms previous graph clustering methods with respect to accuracy.
Starting Page	91
Ending Page	100
File Size	334727
Page Count	10
File Format	PDF
ISBN	9781424452422
ISSN	15504786
DOI	10.1109/ICDM.2009.39
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological system modeling Clustering algorithms Algorithm design and analysis Availability Complex networks Heuristic algorithms Character generation Fungi Proteins Clustering methods graph clustering flow-based approach biological networks
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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