ACOPIN: An ACO algorithm with TSP approach for clustering proteins from protein interaction network

Proceedings - EMS 2008, European Modelling Symposium, 2nd UKSim European Symposium on Computer Modelling and Simulation

Volumn , Issue , 2008, Pages 203-208

  Sallim, Jamaludin ^a   Abdullah, Rosni ^a   Khader, Ahamad Tajudin ^a  

^a SCHOOL OF PHYSICS   (Malaysia)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE NETWORKS; COMPUTER SYSTEMS; FLOW INTERACTIONS; FLOW OF SOLIDS; MAGNETIC PROPERTIES; MAGNETIC SUSCEPTIBILITY; OPTIMIZATION; PROTEINS; TRAVELING SALESMAN PROBLEM;

ACO ALGORITHMS; ANT COLONY OPTIMIZATION ALGORITHMS; CLUSTERING PROBLEMS; PROTEIN INTERACTION NETWORKS; TRAVELING SALESMAN;

CLUSTERING ALGORITHMS;

EID: 55849135545     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMS.2008.94     Document Type: Conference Paper

References (18)

1. J. Sallim, R. Abdullah, and A. T. Abdul Khader, Data Pre-Processing Methodology for Computational Experiment in Analyzing Protein Interaction Networks, Second IEEE Asia Modeling Symposium (AMS 2008), 13-15 May 2008, pp. 843-845.
2. N. Przulj, D.A. Wigle, and I. Junsica. Functional topology in a network of protein interactions. Bioinformatics, 20(3), 2004, pp. 340-348.
3. st International conference on machine learning (ICML'04), Banff, Canada, 2004, pp. 169-176.
4. O. Johnson and J. Liu, A Traveling Salesman Approach for predicting protein functions. Source Code for Biology and Medicine 2006, 1:3, 2006.
5. S. Climer and W Zhang, Rearrangement clustering: Pitfalls, remedies and applications. Journal of Machine Learning of Machine Learning Research in press. http://www.cse.wustl.edu/~sclimer/paper08.pdf
6. J.K. Lenstra and AHGR Kan, Some simple applications of the traveling salesman problem. Oper Res Quant 26, 1975, pp. 717-733.
7. M. Dorigo and T. Stuetzle, Ant Colony Optimization, MIT Press/Bradford Books, Cambridge, MA 2004.
8. S. Lin and B. W. Kernighan, An Effective Heuristic Algorithm for the Traveling-Salesman Problem. Operations Res. 21, 1973, pp. 498-516.
9. M. Dorigo, V. Maniezzo, and A. Colorni, The ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics-Part B 26(1). 1996.
10. http://dip.doe-mbi.ucla.edu/dip/Stat.cgi Access on November 2007.
11. G. Csárdi and T. Nepusz, The igraph software package for complex network research. InterJournal Complex Systems, 1695, 2006. http://cneurocvs. rmki.kfki.hu/igraph/
12. Thomas Stuetzle. ACOTSP, Version 1.0. Available from http://www.aco- metaheuristic.org/aco-code, 2004.
13. S. Asur, et al., An ensemble framework for clustering protein-protein interaction networks. Bioinformatics, 23 ISMB/ECCB 2007, 2007, pp. i29 - i40.
14. V. Arnau, et al., Iterative cluster analysis of protein interaction data. Bioinformatics, 21, 2005, pp. 364-378.
15. Ucar et al., Effective Pre-Processing Strategies for Functional Clustering of a Protein-Protein Interactions Network. BIBE2005, 2005. pp. 129-136.
16. M. Ashburner. et al., Gene Ontology: Tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet., 25, 2000, pp. 25-29.
17. http://geneontology.org
18. http://db.yeastgenome.org/cgi-bin/GO/goTermFinder.