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Protein–Protein Interaction Network Analysis Using NetworkX

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Protein-Protein Interactions

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2690))

Abstract

In recent years, extracting information from biological data has become a particularly valuable way of gaining knowledge. Molecular interaction networks provide a framework for visualizing cellular processes, but their complexity frequently makes their interpretation difficult. Proteins are one of the primary determinants of biological function. Indeed, most biological activities in the living cells are functionally regulated by protein–protein interactions (PPIs). Thus, studying protein interactions is critical for understanding their roles within the cell. Exploring the PPI networks can open new avenues for future experimental studies and offer interspecies predictions for effective interaction map**. In this chapter we will demonstrate how to construct, visualize, and analyze a protein–protein interaction network using NetworkX.

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Acknowledgments

This research was funded by the National Science Foundation (IOS-2038872).

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Authors and Affiliations

  1. Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA

    Mehadi Hasan, Nilesh Kumar, Aqsa Majeed & Shahid Mukhtar

  2. Department of Anesthesiology and Perioperative Medicine, Birmingham, AL, USA

    Aftab Ahmad

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  1. Mehadi Hasan
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  2. Nilesh Kumar
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  3. Aqsa Majeed
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  4. Aftab Ahmad
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  5. Shahid Mukhtar
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Corresponding author

Correspondence to Shahid Mukhtar .

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Editors and Affiliations

  1. Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA

    Shahid Mukhtar

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Hasan, M., Kumar, N., Majeed, A., Ahmad, A., Mukhtar, S. (2023). Protein–Protein Interaction Network Analysis Using NetworkX. In: Mukhtar, S. (eds) Protein-Protein Interactions. Methods in Molecular Biology, vol 2690. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3327-4_35

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  • DOI: https://doi.org/10.1007/978-1-0716-3327-4_35

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3326-7

  • Online ISBN: 978-1-0716-3327-4

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