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A survey of computational methods in protein–protein interaction networks

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  • Saeid Rasti

    (North Dakota State University)

  • Chrysafis Vogiatzis

    (North Carolina A&T State University)

Abstract

Protein–protein interaction networks are mathematical constructs where every protein is represented as a node, with an edge signaling that two proteins interact. These constructs have enabled a series of graph theoretic computational methods in the analysis of how cell life works. Such methods have found diverse applications from helping create more reliable interaction data, to identifying new protein complexes and predict their functionalities, and investigating the minimum requirements for cell life through protein essentiality. Our goal with this survey is to provide an overview of the research in the area from a network analysis perspective. In this work, we provide a brief introduction to protein–protein interaction networks, followed by the methods that we currently have to obtain such interactions and the databases they can be found at. Then, we proceed to discuss the network properties of protein–protein interaction networks and how they can be exploited to identify protein complexes and functional modules, as well as help classify proteins as essential. We finish this survey with a full bibliography on work in protein–protein interactions that could be of interest to operations research and computational science academicians and practitioners.

Suggested Citation

  • Saeid Rasti & Chrysafis Vogiatzis, 2019. "A survey of computational methods in protein–protein interaction networks," Annals of Operations Research, Springer, vol. 276(1), pages 35-87, May.
  • Handle: RePEc:spr:annopr:v:276:y:2019:i:1:d:10.1007_s10479-018-2956-2
    DOI: 10.1007/s10479-018-2956-2
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    References listed on IDEAS

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    4. Benjamin A Shoemaker & Anna R Panchenko, 2007. "Deciphering Protein–Protein Interactions. Part II. Computational Methods to Predict Protein and Domain Interaction Partners," PLOS Computational Biology, Public Library of Science, vol. 3(4), pages 1-7, April.
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    6. Anton J. Enright & Ioannis Iliopoulos & Nikos C. Kyrpides & Christos A. Ouzounis, 1999. "Protein interaction maps for complete genomes based on gene fusion events," Nature, Nature, vol. 402(6757), pages 86-90, November.
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    Cited by:

    1. Mustafa C. Camur & Thomas Sharkey & Chrysafis Vogiatzis, 2022. "The Star Degree Centrality Problem: A Decomposition Approach," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 93-112, January.
    2. Camur, Mustafa C. & Sharkey, Thomas C. & Vogiatzis, Chrysafis, 2023. "The stochastic pseudo-star degree centrality problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 525-539.

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