Name
Title | ||
|---|---|---|
A Comprehensive Review And Evaluation Of Computational Methods For Identifying Protein Complexes From Protein-Protein Interaction Networks |
Abstract | ||
|---|---|---|
Protein complexes are the fundamental units for many cellular processes. Identifying protein complexes accurately is critical for understanding the functions and organizations of cells.With the increment of genome-scale protein-protein interaction (PPI) data for different species, various computational methods focus on identifying protein complexes from PPI networks. In this article, we give a comprehensive and updated review on the state-of-the-art computational methods in the field of protein complex identification, especially focusing on the newly developed approaches. The computational methods are organized into three categories, including cluster-quality-based methods, node-affinity-based methods and ensemble clustering methods. Furthermore, the advantages and disadvantages of different methods are discussed, and then, the performance of 17 state-of-the-art methods is evaluated on two widely used benchmark data sets. Finally, the bottleneck problems and their potential solutions in this important field are discussed. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1093/bib/bbz085 | BRIEFINGS IN BIOINFORMATICS |
Keywords | DocType | Volume |
protein complexes, protein-protein interaction networks, cluster-quality-based methods, node-affinity-based methods, ensemble clustering methods | Journal | 21 |
Issue | ISSN | Citations |
5 | 1467-5463 | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhourun Wu | 1 | 1 | 0.35 |
| Qing Liao | 2 | 37 | 11.60 |
| Bin Liu | 3 | 419 | 33.30 |