Name
Title | ||
|---|---|---|
Idenpc-Miip: Identify Protein Complexes From Weighted Ppi Networks Using Mutual Important Interacting Partner Relation |
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/bib/bbaa016 | BRIEFINGS IN BIOINFORMATICS |
Keywords | DocType | Volume |
protein complexes, protein-protein interaction networks, mutual important interacting partner relation | Journal | 22 |
Issue | ISSN | Citations |
2 | 1467-5463 | 2 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhourun Wu | 1 | 2 | 0.35 |
| Qing Liao | 2 | 37 | 11.60 |
| Bin Liu | 3 | 419 | 33.30 |