Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward.

ABSTRACT: Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysi

SUBMITTER: Omranian S 

PROVIDER: S-EPMC9166428 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature