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Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7 by Xia Wang; Junjie Yue; Xianwen Ren; Yuelan Wang; Mingfeng Tan; Beiping Li; Long Liang is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7 about?
## Background With the development of experimental techniques and bioinformatics, the quantity of data available from protein-protein interactions (PPIs) is increasing exponentially. Functional modules can be identified from protein interaction networks. It follows that the investigation of functional modules will generate a better understanding of cellular organization, processes, and functions. However, experimental PPI data are still limited, and no modularity analysis of PPIs in pathogens has been published to date. ## Results In this study, we predict and analyze the functional modules of __E. coli__ O157:H7 systemically by integrating several bioinformatics methods. After evaluation, most of the predicted modules are found to be biologically significant and functionally homogeneous. Six pathogenicity-related modules were discovered and analyzed, including novel modules. These modules provided new information on the pathogenicity of O157:H7. The modularity of cellular function and cooperativity between modules are also discussed. Moreover, modularity analysis of O157:H7 can provide possible candidates for biological pathway extension and clues for discovering new pathways of c
Who reads Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Xia Wang; Junjie Yue; Xianwen Ren; Yuelan Wang; Mingfeng Tan; Beiping Li; Long Liang
- Publisher
- BioMed Central; Springer (Biomed Central Ltd.); [London]: BioMed Central, 2004-; Springer Science and Business Media LLC (ISSN 1742-4682)
- Published
- 2011
- Language
- EN
- ISBN
- 9781742468303
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)