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Identifying responsive functional modules from protein-protein interaction network

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Molecules and Cells

Abstract

Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.

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Authors and Affiliations

  1. Institute of Systems Biology, Shanghai University, Shanghai, 200444, China

    Zikai Wu, Xingming Zhao & Luonan Chen

  2. School of Communication and Information Engineering, Shanghai University, Shanghai, China

    Zikai Wu

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  1. Zikai Wu
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  2. Xingming Zhao
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  3. Luonan Chen
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Correspondence to Luonan Chen.

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Wu, Z., Zhao, X. & Chen, L. Identifying responsive functional modules from protein-protein interaction network. Mol Cells 27, 271–277 (2009). https://doi.org/10.1007/s10059-009-0035-x

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