MEET: Motif elements estimation toolkit

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 6483-6486

  Pairó, Erola ^a,c   Maynou, Joan ^b   Vallverdú, Montserrat ^b   Caminal, Pere ^b   Marco, Santiago ^a,c   Perera, Alexandre ^b  

^a INSTITUTE FOR BIOENGINEERING OF CATALONIA IBEC   (Spain)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c UNIVERSITY OF BARCELONA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALIGNMENT ALGORITHMS; DETECTION ALGORITHM; DETECTION METHODS; DETECTION MODE; DETECTION MODELS; EXPECTATION MAXIMIZATION; MOTIF DISCOVERY; MULTIPLE SEQUENCES; SEARCHING ALGORITHMS; TRAINING MODE; TRANSCRIPTION FACTOR BINDING SITES;

ALIGNMENT; BINDING SITES; DETECTORS; INFORMATION THEORY; TRANSCRIPTION FACTORS;

ALGORITHMS;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; BINDING SITE; BIOLOGY; COMPUTER LANGUAGE; COMPUTER PROGRAM; DNA SEQUENCE; FUNGAL GENE; GENETICS; GENOME; METHODOLOGY; PROBABILITY; PROMOTER REGION; PROTEIN MOTIF; RECEIVER OPERATING CHARACTERISTIC; SACCHAROMYCES CEREVISIAE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID MOTIFS; AREA UNDER CURVE; BINDING SITES; COMPUTATIONAL BIOLOGY; GENES, FUNGAL; GENOME; PROBABILITY; PROGRAMMING LANGUAGES; PROMOTER REGIONS, GENETIC; ROC CURVE; SACCHAROMYCES CEREVISIAE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 84055191968     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6091600     Document Type: Conference Paper

References (14)

1. R. Mutihac, A. Cicuttin, and R. Mutihac, "Entropic approach to information coding in dna molecules," Materials Science & Engineering C, vol. 18, no. 1-2, pp. 51-60, 2001.
2. T. Lee, N. Rinaldi, F. Robert, D. Odom, Z. Bar-Joseph, G. Gerber, N. M. Hannett, C. T. Harbison, M. Thompson, I. Simon, J. Zeitlinger, E. Jennings, H. Murray, D. Gordon, B. Ren, J. Wyrick, J. Tagne, T. Volkert, E. Fraenkel, D. Gifford, and R. A. Young, "Transcriptional regulatory networks in saccharomyces cerevisiae," Science, vol. 298, pp. 799-804, 2002.
3. W. Wei and X.-D. Yu, "Comparative analysis of regulatory motif discovery tools for transcription factor binding sites," Geno. Prot. Bioinfo., vol. 5, 2007.
4. M. K. Das and H.-K. Dai, "A survay of dna motif finding algorithms," BMC Bioinformatics, vol. 8(Suppl 7), p. S21, 2007.
5. T. Bailey and C. Elkan, "Fitting a mixture model by expectation maximization to discover motifs in biopolymers," in Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology. AAAI Press, August 1994, pp. 28-36.
6. J. Maynou, J.-J. Gallardo-Chacon, M. Vallverdu, P. Caminal, and A. Perera, "Computational detection of transcription factor binding sites through differential rényi entropy," Information Theory, IEEE Transactions on, vol. 56, no. 2, pp. 734 -741, feb. 2010.
7. A. Kel, E. Gossling, I. Reuter, E. Cheremushkin, O. Kel-Margoulis, and E. Wingender, "MATCHTM: a tool for searching transcription factor binding sites in DNA sequences," Nucl. Acids Res., vol. 31, no. 13, pp. 3576-3579, 2003.
8. T. Bailey and G. Michael, "Combining evidence using p-values: application to sequence homology searches," Bioinformatics, vol. 14, pp. 48-54, 1998.
9. A. Rényi, "On measures of entropy and information," in Proc. 4th Berkeley Simposium on Mathematics, Statistics and Probability, 1961, pp. 547-561.
10. S. Kullback and R. A. Leibler, "On information and sufficiency," Ann.Math. Stat, vol. 22, pp. 79-86, 1951.
11. E. Pairo, S. Marco, and A. Perera, "A subspace method for the detection of transcripction factor binding sites." in Proc. of the 1st International Conference IEEE International Conference on BioInformatics, 20-23 Jan. 2009, pp. 1-5.
12. R. C. Edgar, "MUSCLE: multiple sequence alignment with high accuracy and high throughput." Nucleic Acids Res, vol. 32, no. 5, pp. 1792-1797, 2004. [Online]. Available: http://dx.doi.org/10.1093/nar/gkh340
13. J. Thompson, D. Higgins, and T. Gibson, "Clustal w: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, positions-specific gap penalties and weight matrix choice," Nucleic Acids Res., vol. 22, pp. 4673-4680, 1994.
14. R Development Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, 2010, ISBN 3-900051-07-0. [Online]. Available: http://www.R-project.org