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This article is part of the supplement: First International Workshop on Text Mining in Bioinformatics (TMBio) 2006

Open Access Proceedings

BioCAD: an information fusion platform for bio-network inference and analysis

Doheon Lee*, Sangwoo Kim and Younghoon Kim

Author Affiliations

Department of Bio and Brain Engineering, KAIST, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon, 305-701, Republic of Korea

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BMC Bioinformatics 2007, 8(Suppl 9):S2  doi:10.1186/1471-2105-8-S9-S2

Published: 27 November 2007

Abstract

Background

As systems biology has begun to draw growing attention, bio-network inference and analysis have become more and more important. Though there have been many efforts for bio-network inference, they are still far from practical applications due to too many false inferences and lack of comprehensible interpretation in the biological viewpoints. In order for applying to real problems, they should provide effective inference, reliable validation, rational elucidation, and sufficient extensibility to incorporate various relevant information sources.

Results

We have been developing an information fusion software platform called BioCAD. It is utilizing both of local and global optimization for bio-network inference, text mining techniques for network validation and annotation, and Web services-based workflow techniques. In addition, it includes an effective technique to elucidate network edges by integrating various information sources. This paper presents the architecture of BioCAD and essential modules for bio-network inference and analysis.

Conclusion

BioCAD provides a convenient infrastructure for network inference and network analysis. It automates series of users' processes by providing data preprocessing tools for various formats of data. It also helps inferring more accurate and reliable bio-networks by providing network inference tools which utilize information from distinct sources. And it can be used to analyze and validate the inferred bio-networks using information fusion tools.