Paper Info
Title
Experimental evaluation of topological-based fitness functions to detect complexes in PPI networks
Abstract
The detection of groups of proteins sharing common biological features is an important research issue, intensively investigated in the last few years, because of the insights it can give in understanding cell behavior. In this paper we present an extensive experimental evaluation campaign aiming at exploring the capability of Genetic Algorithms (GAs) to find clusters in protein-protein interaction networks, when different topological-based fitness functions are employed. A complete experimentation on the yeast protein-protein interaction network, along with a comparative evaluation of the effectiveness in detecting true complexes on the yeast and human networks, reveals GAs as a feasible and competitive computational technique to cope with this problem.
Year
DOI
Venue
2012
10.1145/2330163.2330191
GECCO
Keywords
Field
DocType
genetic algorithms,extensive experimental evaluation campaign,ppi network,complete experimentation,protein-protein interaction network,common biological feature,different topological-based fitness function,yeast protein-protein interaction network,cell behavior,competitive computational technique,comparative evaluation,genetic algorithm,fitness function
Protein protein interaction network,Computational Technique,Cluster (physics),Topology,Computer science,Interaction network,Artificial intelligence,Machine learning,Genetic algorithm
Conference
Citations 
PageRank 
References 
5
0.40
15
Authors
2
Name
Order
Citations
PageRank
Clara Pizzuti11250122.13
Simona E. Rombo219222.21