idenPC-MIIP: identify protein complexes from weighted PPI networks using mutual important interacting partner relation.
basic_science · Level V
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- Record sourced from PubMed, PMID 32065215.
- Also identified by DOI 10.1093/bib/bbaa016.
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Abstract
Protein complexes are key units for studying a cell system. During the past decades, the genome-scale protein-protein interaction (PPI) data have been determined by high-throughput approaches, which enables the identification of protein complexes from PPI networks. However, the high-throughput approaches often produce considerable fraction of false positive and negative samples. In this study, we propose the mutual important interacting partner relation to reflect the co-complex relationship of two proteins based on their interaction neighborhoods. In addition, a new algorithm called idenPC-MIIP is developed to identify protein complexes from weighted PPI networks. The experimental results on two widely used datasets show that idenPC-MIIP outperforms 17 state-of-the-art methods, especially for identification of small protein complexes with only two or three proteins.
Medical subject headings
- Computational Biology
- Protein Interaction Maps