Name
Abstract | ||
|---|---|---|
We propose a binary matrix factorization (BMF) algorithm under the Bayesian Ying-Yang (BYY) harmony learning, to detect protein complexes by clustering the proteins which share similar interactions through factorizing the binary adjacent matrix of the protein-protein interaction (PPI) network. The proposed BYY-BMF algorithm automatically determines the cluster number while this number is usually specified for most existing BMF algorithms. Also, BYY-BMF's clustering results does not depend on any parameters or thresholds, unlike the Markov Cluster Algorithm (MCL) that relies on a so-called inflation parameter. On synthetic PPI networks, the predictions evaluated by the known annotated complexes indicate that BYY-BMF is more robust than MCL for most cases. Moreover, BYY-BMF obtains a better balanced prediction accuracies than MCL and a spectral analysis method, on real PPI networks from the MIPS and DIP databases. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/BIBMW.2010.5703783 | 2010 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW) |
DocType | ISSN | Citations |
Conference | 2163-6966 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shikui Tu | 1 | 39 | 14.25 |
| Lei Xu | 2 | 3590 | 387.32 |
| Runsheng Chen | 3 | 404 | 31.48 |