Abstract
In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.
| Language | English |
|---|---|
| Pages | 290-306 |
| Number of pages | 17 |
| Journal | International Journal of Computational Biology and Drug Design |
| Volume | 4 |
| Issue number | 3 |
| Early online date | 21 Jul 2011 |
| DOIs | |
| Publication status | Published - 31 Jul 2011 |
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Keywords
- Graph clustering
- PPIs
- Protein-protein interactions
- Random walks
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Detection of functional modules from protein interaction networks with an enhanced random walk based algorithm. / Cai, Bingjing; Wang, Haiying; Zheng, Huiru; Wang, Hui.
In: International Journal of Computational Biology and Drug Design, Vol. 4, No. 3, 31.07.2011, p. 290-306.Research output: Contribution to journal › Article
TY - JOUR
T1 - Detection of functional modules from protein interaction networks with an enhanced random walk based algorithm
AU - Cai, Bingjing
AU - Wang, Haiying
AU - Zheng, Huiru
AU - Wang, Hui
PY - 2011/7/31
Y1 - 2011/7/31
N2 - In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.
AB - In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.
KW - Graph clustering
KW - PPIs
KW - Protein-protein interactions
KW - Random walks
UR - http://www.scopus.com/inward/record.url?scp=80555133193&partnerID=8YFLogxK
U2 - 10.1504/IJCBDD.2011.041416
DO - 10.1504/IJCBDD.2011.041416
M3 - Article
VL - 4
SP - 290
EP - 306
JO - International Journal of Computational Biology and Drug Design
T2 - International Journal of Computational Biology and Drug Design
JF - International Journal of Computational Biology and Drug Design
SN - 1756-0756
IS - 3
ER -