Identifying conserved discriminative motifs

Jyotsna Kasturi; Raj Acharya; Ross Hardison

doi:10.1007/978-3-540-88436-1_29

Identifying conserved discriminative motifs

Jyotsna Kasturi, Raj Acharya, Ross Hardison

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The identification of regulatory motifs underlying gene expression is a challenging problem, particularly in eukaryotes. An algorithm to identify statistically significant discriminative motifs that distinguish between gene expression clusters is presented. The predictive power of the identified motifs is assessed with a supervised Naïve Bayes classifier. An information-theoretic feature selection criterion helps find the most informative motifs. Results on benchmark and real data demonstrate that our algorithm accurately identifies discriminative motifs. We show that the integration of comparative genomics information into the motif finding process significantly improves the discovery of discriminative motifs and overall classification accuracy.

Original language	English (US)
Title of host publication	3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
Publisher	Springer Verlag
Pages	334-348
Number of pages	15
ISBN (Print)	3540884343, 9783540884347
DOIs	https://doi.org/10.1007/978-3-540-88436-1_29
State	Published - 2008
Event	3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008 - Melbourne, VIC, Australia Duration: Oct 15 2008 → Oct 17 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5265 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
Country/Territory	Australia
City	Melbourne, VIC
Period	10/15/08 → 10/17/08

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-88436-1_29

Cite this

Kasturi, J., Acharya, R., & Hardison, R. (2008). Identifying conserved discriminative motifs. In 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008 (pp. 334-348). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5265 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-540-88436-1_29

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title = "Identifying conserved discriminative motifs",

abstract = "The identification of regulatory motifs underlying gene expression is a challenging problem, particularly in eukaryotes. An algorithm to identify statistically significant discriminative motifs that distinguish between gene expression clusters is presented. The predictive power of the identified motifs is assessed with a supervised Na{\"i}ve Bayes classifier. An information-theoretic feature selection criterion helps find the most informative motifs. Results on benchmark and real data demonstrate that our algorithm accurately identifies discriminative motifs. We show that the integration of comparative genomics information into the motif finding process significantly improves the discovery of discriminative motifs and overall classification accuracy.",

author = "Jyotsna Kasturi and Raj Acharya and Ross Hardison",

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year = "2008",

doi = "10.1007/978-3-540-88436-1_29",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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address = "Germany",

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Kasturi, J, Acharya, R & Hardison, R 2008, Identifying conserved discriminative motifs. in 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5265 LNBI, Springer Verlag, pp. 334-348, 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008, Melbourne, VIC, Australia, 10/15/08. https://doi.org/10.1007/978-3-540-88436-1_29

Identifying conserved discriminative motifs. / Kasturi, Jyotsna; Acharya, Raj; Hardison, Ross.
3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008. Springer Verlag, 2008. p. 334-348 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5265 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Acharya, Raj

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N2 - The identification of regulatory motifs underlying gene expression is a challenging problem, particularly in eukaryotes. An algorithm to identify statistically significant discriminative motifs that distinguish between gene expression clusters is presented. The predictive power of the identified motifs is assessed with a supervised Naïve Bayes classifier. An information-theoretic feature selection criterion helps find the most informative motifs. Results on benchmark and real data demonstrate that our algorithm accurately identifies discriminative motifs. We show that the integration of comparative genomics information into the motif finding process significantly improves the discovery of discriminative motifs and overall classification accuracy.

AB - The identification of regulatory motifs underlying gene expression is a challenging problem, particularly in eukaryotes. An algorithm to identify statistically significant discriminative motifs that distinguish between gene expression clusters is presented. The predictive power of the identified motifs is assessed with a supervised Naïve Bayes classifier. An information-theoretic feature selection criterion helps find the most informative motifs. Results on benchmark and real data demonstrate that our algorithm accurately identifies discriminative motifs. We show that the integration of comparative genomics information into the motif finding process significantly improves the discovery of discriminative motifs and overall classification accuracy.

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DO - 10.1007/978-3-540-88436-1_29

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SN - 9783540884347

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Kasturi J, Acharya R, Hardison R. Identifying conserved discriminative motifs. In 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008. Springer Verlag. 2008. p. 334-348. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-88436-1_29

Identifying conserved discriminative motifs

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