ArticleComputational and structural biotechnology journal2021
Efficient and accurate identification of protein complexes from protein-protein interaction networks based on the clustering coefficient.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- In Silico Analysis Reveals MDM2 as a Potential Target of Ursolic Acid for Overcoming Tamoxifen Resistance in Breast Cancer.Asian Pacific journal of cancer prevention : APJCP · 2025Article
- PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information.Briefings in bioinformatics · 2024Article
- LazyFox: fast and parallelized overlapping community detection in large graphs.PeerJ. Computer science · 2023Article
- Detecting protein complexes with multiple properties by an adaptive harmony search algorithm.BMC bioinformatics · 2022Article
- Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward.Computational and structural biotechnology journal · 2022Review
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Authors and funding
3 authors.
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Abstract
Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from
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