Community Detection in Protein-Protein Interaction Networks and Applications

The ability to identify and characterize not only the protein-protein interactions but also their internal modular organizationthrough network analysis is fundamental for understanding the mechanisms of biological processes at the molecular level. Indeed, thedetection of the network communities can enhance our understanding of the molecular basis of disease pathology, and promote drugdiscovery and disease treatment in personalized medicine. This work gives an overview of recent computational methods for thedetection of protein complexes and functional modules in protein-protein interaction networks, also providing a focus on some of itsapplications. We propose a systematic reformulation of frequently adopted taxonomies for these methods, also proposing newcategories to keep up with the most recent research. We review the literature of the last five years (2017-2021) and provide links toexisting data and software resources. Finally, we survey recent works exploiting module identification and analysis, in the context of avariety of disease processes for biomarker identification and therapeutic target detection. Our review provides the interested readerwith an up-to-date and self-contained view of the existing research, with links to state-of-the-art literature and resources, as well ashints on open issues and future research directions in complex detection and its applications.