Paper Info
Title
Firefly Clustering Method for Mining Protein Complexes.
Abstract
It is a hot research to explore protein complexes which are closely related to biological processes from the biological network. As a novel swarm intelligence optimization algorithm, the firefly algorithm (FA) has been verified to solve many optimization problems. In this study, we transform the protein clustering problem into an optimization problem in protein-protein interaction (PPI) network. A new method for mining protein complexes based on the firefly algorithm was proposed, called FC. A new objective function was proposed to find the high cohesion and low coupling clusters. A thorough comparison completed for different protein clustering methods has been carried out. The clustering results show that FC method outperforms the other state-of-the-art methods in accuracy of detecting complexes from PPI network.
Year
DOI
Venue
2017
10.1007/978-3-319-61824-1_65
ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT I
Keywords
Field
DocType
Firefly clustering,Protein complexes,Dynamic PPI network,Clustering objective function
Data mining,Computer science,Biological network,Cohesion (computer science),Swarm intelligence,Firefly algorithm,Artificial intelligence,Cluster analysis,Optimization problem,Firefly protocol,Coupling (computer programming),Machine learning
Conference
Volume
ISSN
Citations 
10385
0302-9743
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Yuchen Zhang186.51
Xiu-juan Lei220735.58
Ying Tan3128695.40