Incorporating heuristics in a swarm intelligence framework for inferring gene regulatory networks from gene expression time series

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5217 LNCS, Issue , 2008, Pages 323-330

  Kentzoglanakis, Kyriakos ^a   Poole, Matthew ^a   Adams, Carl ^a  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AMPLIFICATION; BIOACTIVITY; CELLULAR AUTOMATA; GENE EXPRESSION; HEURISTIC METHODS; PARTICLE SWARM OPTIMIZATION (PSO); STRUCTURAL OPTIMIZATION; TIME SERIES ANALYSIS;

AMPLIFICATION EFFECTS; ANT SYSTEMS; CANDIDATE NETWORKS; DATA SETS; DO-MAINS; GENE REGULATORY NETWORKS; PARTICLE SWARM OPTIMIZATION ALGORITHMS; REAL WORLDS; SWARM INTELLIGENCES; TIME SERIES;

OPTIMIZATION;

EID: 56449091133     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87527-7_33     Document Type: Conference Paper

References (18)

1. Alon, U.: An introduction to systems biology: design principles of biological circuits. Chapman & Hall/CRC, Boca Raton (2007)
2. Kitano, H.: Computational systems biology. Nature 420, 206-210 (2002)
3. Husmeier, D.: Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. Bioinformatics 19(17), 2271-2282 (2003)
4. Ressom, H., Zhang, Y., Xuan, J., Wang, Y., Clarke, R.: inference of gene regulatory networks from time course gene expression data using neural networks and swarm intelligence. in: IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, pp. 1-8 (2006)
5. Eisen, M., Spellman, P., Brown, P., Botstein, D.: Cluster analysis and display of genome-wide expression patterns. PNAS 95(25), 14863-14868 (1998)
6. D'Haeseleer, P., Wen, X., Fuhrman, S.: Mining the gene expression matrix: inferring gene relationships from large scale gene expression data. In: Second international Workshop on Information Processing in Cell and Tissues, pp. 203-212 (1998)
7. de Jong, H.: Modeling and simulation of genetic regulatory systems: a literature review. Journal of Computational Biology 9(1), 69-105 (2002)
8. Somogyi, R., Fuhrman, S., Askenazi, M.: The gene expression matrix: towards the extraction of genetic network architectures. Nonlinear Analysis, Theory, Methods & Applications 30(3), 1815-1824 (1997)
9. Perrin, B., Ralaivola, L., Mazurie, A., Bottani, S., Mallet, J., d'Alche Bue, F.: Gene networks inference using dynamic Bayesian networks. Bioinformatics 19(suppl. 2), ii 138-ii 148 (2003)
10. Vohradsky, J.: Neural model of the genetic network. Journal of Biological Chemistry 276(39), 36168-36173 (2001)
11. Wahde, M., Hertz, J.: Modeling Genetic Regulatory Dynamics in Neural Development. Journal of Computational Biology 8(4), 429-442 (2001)
12. Pournara, I., Wernisch, L.: Factor analysis for gene regulatory networks and transcription factor activity profiles. BMC Bioinformatics 8(61) (2007)
13. Xu, R., Wunsch, D.C.I., Frank, R.: Inference of genetic regulatory networks with recurrent neural network models using particle swarm optimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4(4), 681-692 (2007)
14. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: from natural to artificial systems. Oxford University Press, Oxford (1999)
15. Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: IEEE International Conference on Neural Networks, vol. 4, pp. 1942-1948 (1995)
16. Kwon, A., Hoos, H., Ng, R.: Inference of transcriptional regulation relationships from gene expression data. Bioinformatics 19(8), 905-912 (2003)
17. Needleman, S., Wunsch, C: A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48, 443-453 (1970)
18. Spellman, P., Sherlock, G., Zhang, M., Iyer, V., Anders, K., Eisen, M., Brown, P.O., Botstein, D., Futcher, B.: Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization. Molecular Biology of the Cell 9, 3273-3297 (1998)