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A Gene Regulatory Network Prediction Method using Particle Swarm Optimization and Genetic Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 83 - Number 12 |
| Year of Publication: 2013 |
| Authors: Abhishek, Shailendra Singh |
10.5120/14502-2388
|
Abhishek, Shailendra Singh . A Gene Regulatory Network Prediction Method using Particle Swarm Optimization and Genetic Algorithm. International Journal of Computer Applications. 83, 12 ( December 2013), 32-37. DOI=10.5120/14502-2388
Abstract
Gene regulatory networks (GRNs) are complex control systems that deal with the interaction of genes, which eventually control cellular processes at the protein level. The investigation of GRN provides huge information on cellular processes and gene functions and at last contributes to knowledge in genetics and in turn quality of life. By understanding the dynamics of these networks using correct and representative methods and models, potentially cover the way for curing diseases, improving diagnostic procedures and producing drug designs with greater impact. In this work a GRN prediction method based on TDCLR using PSO and GA is proposed to construct GRN from microarray datasets. TDCLR is used to find the directions of information flow between different gene pairs. The proposed method uses the particle swarm optimization (PSO) to find thresholds for discretizing the microarray dataset and genetic algorithm (GA) is used to generate a set of fit candidate gene pair from which GRN is constructed. The sub-network containing five genes of S. cerevisiae (yeast) is used to evaluate the accuracy of the proposed method. The experimental results show that the proposed method is better than TDCLR and other existing methods such as mutual information (MI) in terms of sensitivity and specificity.
References
- S. P. Li, J. J. Tseng, S. C. Wang, Reconstructing gene regulatory networks from time-series microarray data, Physica A 350 (2005) 63–69.
- Harri Lahdesmaki, Sampsa Hautaniemi , Ilya Shmulevich ,Olli Yli-Harja "Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks"Science Direct 2006.
- Raed I. Hamed, S. I. Ahson, R. Parveen "A New Approach for Modelling Gene Regulatory Networks Using Fuzzy Petri Nets" Journal of Integrative Bioinformatics, 7(1):113, 2010.
- Akther Shermin, Mehmet A. Orun" Using Dynamic Bayesian Networks to Infer Gene Regulatory Networks from Expression Profiles"acm 2009.
- R. Eriksson, B. Olsson, Adapting genetic regulatory models by genetic programming, Biosystems 76 (2004) 217–227
- R. Linden, A. Bhaya, Evolving fuzzy rules to model gene expression, Biosystems
- Wentian Li" Mutual Information Functions Versus Correlation Functions" Journal of Statistical Physics, 60(5-6):823-837 (1990)
- Vijender Chaitankar, Preetam Ghosh, et al. "sCoIn: A Scoring algorithm based on COmplex INteractions for reverse engineering regulatory networks" Proceedings of the 2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), Larnaca, Cyprus, 11-13 November 2012
- Yao Fu , Laura R Jarboe and Julie A Dickerson "Reconstructing genome-wide regulatory network Of E. coliusing transcriptome data and predicted transcription factor activities" BMC Bioinformatics 2011,12:233
- Seung-Hyun Jin, Peter Lin, and Mark Hallett" Linear and nonlinear information flow based on time delayed mutual information method and its application to corticomuscular interaction" Clin Neurophysiol. 2010 March ; 121(3): 392. doi:10. 1016/j. clinph. 2009. 09. 033
- Kaletaet al. "Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis" BMC Systems Biology2010,4:116
- Patrick E. Meyer et al. "Information-Theoretic Inference of Gene Networks Using Backward Elimination"
- Nagwan M. Abdel Samee, Nahed H. Solouma , Yasser M. Kadah "Gene Network Construction and Pathways Analysis for High Throughput Microarrays" 29th National Radio Science Conference (NRSC 2012)
- Vijender Chaitankar et al. "Gene Regulatory Network Inference Using Time Lagged Context Likelihood of Relatedness" 2011 IEEE
- Ioan Cristian Trelea "The particle swarm optimization algorithm: convergence analysis and parameter selection" Information Processing Letters 85 (2003) 317–325 2002 Elsevier Science
- Riccardo Poli, James Kennedy, Tim Blackwell " Particle swarm optimization: An overview" Swarm Intell (2007) 1: 33–57 DOI 10. 1007/s11721-007-0002-0
- Chien-Pang Lee, Yungho Leu, Wei-Ning Yang "Constructing gene regulatory networks from microarray data using GA/PSO with DTW" Applied Soft Computing 12 (2012) 1115–1124, 2011 Elsevier.
- Z. Huang et al. " Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining", Decis. Support Syst. 43 (2007) 1207–1225.
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