Summary
We present a new, efficient and scalable tool, named BIORED, for pattern discovery in proteomic and genomic sequences. It uses a genetic algorithm to find interesting patterns in the form of regular expressions, and a new efficient pattern matching procedure to count pattern occurrences. We studied the performance, scalability and usefulness of BIORED using several databases of biosequences. The results show that BIORED was successful in finding previously known patterns, thus an excellent indicator for its potential. BIORED is available for download under the GNU Public License at http://www.dcc.fc.up.pt/biored/ . An online demo is available at the same address.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs (Third, Revised and Extended edn.). Springer, New York (1999)
van Helden, J., del Olmo, M., Perez-Ortin, J.: Statistical analisys of yeast genome downstream sequences reveals putative polyadenylation signals. Nucleic Acids Research 28(4), 1000–1010 (2000)
Sinha, S., Tompa, M.: A statistical method for finding transcription factor binding sites. Proceedings of the National Academy of Sciences of the United States of America 95(6), 2738–2743 (2000)
Sinha, S., Tompa, M.: An exact method for finding shor motifs in sequences, with application to the ribosome binding site problem. In: Proceedings of the 7th International Conference on ISMB, pp. 262–271 (1999)
Feller, W.: An Introduction to Probability Theory and Its Applications, 3rd edn. John Wiley & Sons, Chichester (1968)
Cole, R., Hariharan, R.: Verifying candidate matches in sparse and wildcard matching. In: STOC 2002: Proceedings of the thiry-fourth annual ACM symposium on Theory of computing, pp. 592–601. ACM Press, New York (2002)
Navarro, G.: Pattern matching. Journal of Applied Statistics 31(8), 925–949 (2004); Special issue on Pattern Discovery
Pereira, P., Fonseca, N.A., Silva, F.: A high performance distributed tool for mining patterns in biological sequences. Technical Report DCC-2006-08, DCC-FC & LIACC, Universidade do Porto (2006)
R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, (2005) ISBN 3-900051-07-0
Hubbard, T., Andrews, D., Caccamo, M., et al.: Ensembl 2005. Nucleic Acids Research 33(1) (January 2005)
Rotwein, P., Yokoyama, S., Didier, D.K., Chirgwin, J.M.: Genetic analysis of the hypervariable region flanking the human insulin gene. The American Journal of Human Genetics (1986)
Lew, A., Rutter, W.J., Kennedy, G.C.: Unusual dna structure of the diabetes susceptibility locus iddm2 and its effect on transcription by the insulin promoter factor pur-1/maz. Proceedings of the National Academy of Sciences of the United States of America 97(23), 12508–12512 (2000)
Costas, J., Vieira, C.P., Casares, F., Vieira, J.: Genomic characterization of a repetitive motif strongly associated with developmental genes in drosophila. BMC Genomics (2003)
Rigoutsos, I., Floratos, A.: Combinatorial pattern discovery in biological sequences: The teiresias algorithm. Bioinformatics 14(1), 55–67 (1998)
Jonassen, I., Collins, J.F., Higgins, D.: Finding flexible patterns in unaligned protein sequences. Protein Science 4(8), 1587–1595 (1995)
Hulo, N., Bairoch, A., Bulliard, V., Cerutti, L., De Castro, E., Langendijk-Genevaux, P.S., Pagni, M., Sigrist, C.J.A.: The prosite database. Nucleic Acids Res., 34 (2006)
Bailey, T.L., Elkan, C.: Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Proceedings of the Second International Conference on ISMB, pp. 28–36. AAAI Press, Menlo Park (1994)
Robin, S., Schbath, S., Vandewalle, V.: Statistical tests to compare motif count exceptionalities. BMC Bioinformatics 8(84) (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pereira, P., Silva, F., Fonseca, N.A. (2009). BIORED - A Genetic Algorithm for Pattern Detection in Biosequences. In: Corchado, J.M., De Paz, J.F., Rocha, M.P., Fernández Riverola, F. (eds) 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008). Advances in Soft Computing, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85861-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-85861-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85860-7
Online ISBN: 978-3-540-85861-4
eBook Packages: EngineeringEngineering (R0)