Abstract
Identification of functional modules in large protein interaction networks is crucial to understand principles of cellular organization, processes and functions. As a protein can perform different functions, functional modules overlap with each other. In this paper, we presented a new algorithm OMFinder for mining overlapping functional modules in protein interaction networks by using graph split and reduction. We applied algorithm OMFinder to the core protein interaction network of budding yeast collected from DIP database. The experimental results showed that algorithm OMFinder detected many significant overlapping functional modules with various topologies. The significances of identified modules were evaluated by using functional categories from MIPS database. Most importantly, our algorithm had very low discard rate compared to other approaches of detecting overlapping modules.
This research was supported in part by the National Natural Science Foundation of China under Grant Nos. 60433020 and 60773111, the Program for New Century Excellent Talents in University No. NCET-05-0683, the Program for Changjiang Scholars and Innovative Research Team in University No. IRT0661.
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Li, M., Wang, J., Chen, J. (2008). A Graph-Theoretic Method for Mining Overlapping Functional Modules in Protein Interaction Networks. In: Măndoiu, I., Sunderraman, R., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2008. Lecture Notes in Computer Science(), vol 4983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79450-9_20
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DOI: https://doi.org/10.1007/978-3-540-79450-9_20
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