Abstract
Many processes in the cell involve interaction among the proteins and determination of the networks of such interactions is of immense importance towards the complete understanding of cellular functions. As the experimental techniques for this purpose are expensive and potentially erroneous, there are many computational methods being put forward for prediction of protein-protein interactions. These methods use different genomic features for indirect inference of protein- protein interactions. As the interaction among two proteins is facilitated by domains, there are many methods being put forward for inference of such interactions using the specificity of assignment of domains to proteins. We present here an heuristic optimization method, particle swarm optimization, which predicts protein-protein interaction by using the domain assignments information. Results are compared with another known method which predicts domain interactions by casting the problem of interactions inference as a maximum satisfiability (MAX-SAT) problem.
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References
Benjamin, A., et al.: Deciphering Protein-Protein Interactions. Part I. Experimental Techniques and Databases. PLoS Comput Biol 3(3) e42 (2007)
Benjamin, A., et al.: Deciphering Protein-Protein Interactions. Part II. Computational Methods to Predict Protein and Domain Interaction Partners. PLoS Comput Biol 3(4) e43 (2007)
Valencia, A., Pazos, F.: Computational methods for the prediction of protein interactions. Current Opinion in Structural Biology 12, 368–373 (2002)
Riley, R., et al.: Inferring Protein Domain Interactions From Databases of Interacting Proteins. Genome Biology 6(R89) (2005)
Deng, M., et al.: Inferring Domain-Domain Interactions From Protin-Protein Interactions. Genome Res 12, 1540–1548 (2002)
Lee, H., et al.: An Integrated Approach to the Prediction of Domain-Domain Interactions. BMC Bioinformatics 7(269) (2006)
Li, X., et al.: Improving domain-based protein interaction prediction using biologically-significant negative dataset. International Journal of Data Mining and Bioinformatics 1(2), 138–149 (2006)
Zhang, Y., et al.: Protein Interaction Inference as a MAX-SAT Problem. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego (2005)
Zhang, Y., et al.: Towards Inferring Protein Interactions: Challenges and Solutions. EURASIP Journal on Applied Signal Processing Article ID 37349 (2006)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. IEEE Int. Conf. on Neural Networks, pp. 1942–1948 (1995)
Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Proc. 6 th Int. Symposium on Micro Machine and Human Science, pp. 39–43 (1995)
Shi, Y., Eberhart, R.: Parameter selection in particle swarm optimization. In: Proc. 7th Annual Conf. on Evolutionary Programming, pp. 591–600 (1998)
Kennedy, J., Eberhart, R.: Swarm Intelligence. Morgan Kaufmann, San Francisco (2001)
Poli, R., et al.: Particle swarm optimization: An overview. Swarm Intelligence (August, 2007)
Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: Proc. IEEE Int. Conf. on Evolutionary Computation, pp. 69–73 (1998)
Gough, J., et al.: SUPERFAMILY:HMMs representing all proteins of known structure. SCOP sequence searches, alignments, and genome assignments. Nucl. Acids Res. 30(1), 268–272 (2002)
Madera, M., et al.: The SUPERFAMILY database in 2004: Additions and improvements. Nucleic Acids Res 32(1), D235–239 (2004)
Salwinski, L., et al.: The Database of Interacting Proteins: 2004 update. NAR 32(Database issue), D449–451 (2004)
The GNU: Linear Programming Kit (version 4.7), http://www.gnu.org/software/glpk/glpk.html
Jansen, R., et al.: A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data. Science 302, 449–453 (2003)
Rhodes, D.R., et al.: Probabilistic model of the human protein-protein interaction network. Nature Biotechnology 23(8), 951–959 (2005)
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Iqbal, M., Freitas, A.A., Johnson, C.G. (2008). Protein Interaction Inference Using Particle Swarm Optimization Algorithm. In: Marchiori, E., Moore, J.H. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2008. Lecture Notes in Computer Science, vol 4973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78757-0_6
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DOI: https://doi.org/10.1007/978-3-540-78757-0_6
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