Discriminative motif optimization based on perceptron training

Bioinformatics

Volumn 30, Issue 7, 2014, Pages 941-948

  Patel, Ronak Y ^a   Stormo, Gary D ^a  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA; TRANSCRIPTION FACTOR;

ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; BINDING SITE; CHEMISTRY; COMPUTER PROGRAM; DROSOPHILA MELANOGASTER; HUMAN; METABOLISM; NUCLEOTIDE SEQUENCE; PROTEIN BINDING; SACCHAROMYCES CEREVISIAE;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BASE SEQUENCE; BINDING SITES; DNA; DROSOPHILA MELANOGASTER; HUMANS; PROTEIN BINDING; SACCHAROMYCES CEREVISIAE; SOFTWARE; TRANSCRIPTION FACTORS;

EID: 84897470108     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt748     Document Type: Article

References (32)

1. Bailey, T.L. (2011) DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics, 27, 1653-1659.
2. Bailey, T.L. and Machanick, P. (2012) Inferring direct DNA binding from ChIP-seq. Nucleic Acids Res., 40, e128.
3. Bewick, V. et al. (2004) Statistics review 13: receiver operating characteristic curves. Crit. Care, 8, 508-512.
4. da Piedade, I. et al. (2009) DISPARE: DIScriminative PAttern REfinement for position weight matrices. BMC Bioinformatics, 10, 388.
5. Davis, I.W. et al. (2012) POWRS: position-sensitive motif discovery. PLoS One, 7, e40373.
6. Elemento, O. et al. (2007) A universal framework for regulatory element discovery across all genomes and data types. Mol. Cell, 28, 337-350.
7. Fauteux, F.O. et al. (2008) Seeder:discriminative seeding DNA motif discovery. Bioinformatics, 24, 2303-2307.
8. Fu, W. et al. (2009) DISCOVER: a feature-based discriminative method for motif search in complex genomes. Bioinformatics, 25, i321-i329.
9. Furey, T.S. (2012) ChIP-seq and beyond: new and improved methodologies to detect and characterize protein-DNA interactions. Nat. Rev. Genet., 13, 840-852.
10. Grzybowski, M. and Younger, J.G. (1997) Statistical methodology: III Receiver operating characteristic (ROC) curves. Acad. Emerg. Med., 4, 818-826.
11. Hartmann, H. et al. (2013) P-value-based regulatory motif discovery using positional weight matrices. Genome Res., 23, 181-194.
12. Huggins, P. et al. (2011) DECOD: fast and accurate discriminative DNA motif finding. Bioinformatics, 27, 2361-2367.
13. Kulakovskiy, I.V. et al. (2010) Deep and wide digging for binding motifs in ChIPSeq data. Bioinformatics, 26, 2622-2623.
14. Leung, H.C.M. and Chin, F.Y.L. (2006) Finding motifs from all sequences with and without binding sites. Bioinformatics, 22, 2217-2223.
15. Li, L. et al. (2007) GAPWM: a genetic algorithm method for optimizing a position weight matrix. Bioinformatics, 23, 1188-1194.
16. Linhart, C. et al. (2008) Transcription factor and microRNA motif discovery: the Amadeus platform and a compendium of metazoan target sets. Genome Res., 18, 1180-1189.
17. Liu, X.S. et al. (2002) An algorithm for finding protein-DNA binding sites with applications to chromatin-immunoprecipitation microarray experiments. Nat. Biotechnol., 20, 835-839.
18. Mason, M.J. et al. (2010) Identification of context-dependent motifs by contrasting ChIP binding data. Bioinformatics, 26, 2826-2832.
19. Redhead, E. and Bailey, T.L. (2007) Discriminative motif discovery in DNA and protein sequences using the DEME algorithm. BMC Bioinformatics, 8, 385.
20. Rosenblatt, F. (1962) Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. Spartan Books, Washington, DC.
21. Sharan, R. and Myers, E.W. (2005) A motif-based framework for recognizing sequence families. Bioinformatics, 21 (Suppl. 1), i387-i393.
22. Shi, J. et al. (2011) AMD, an automated motif discovery tool using stepwise refinement of gapped consensuses. PLoS One, 6, e24576.
23. Siddharthan, R. (2008) PhyloGibbs-MP: module prediction and discriminative motif-finding by Gibbs sampling. PLoS Comput. Biol., 4, e1000156.
24. Sinha, S. (2003) Discriminative motifs. J. Comput. Biol., 10, 599-615.
25. Sinha, S. (2006) On counting position weight matrix matches in a sequence, with application to discriminative motif finding. Bioinformatics, 22, e454-e463.
26. Smith, A.D. et al. (2005) Identifying tissue-selective transcription factor binding sites in vertebrate promoters. Proc. Natl Acad. Sci. USA, 102, 1560-1565.
27. Stormo, G.D. et al. (1982) Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E coli. Nucleic Acids Res., 10, 2997-3011.
28. Stormo, G.D. and Zhao, Y. (2010) Determining the specificity of protein-DNA interactions. Nat. Rev. Genet., 11, 751-760.
29. Thomas-Chollier, M. et al. (2011) RSAT peak-motifs: motif analysis in full-size ChIP-seq datasets. Nucleic Acids Res., 40, e31.
30. Thomas-Chollier, M. et al. (2012) A complete workflow for the analysis of fullsize ChIP-seq (and similar) data sets using peak-motifs. Nat. Protoc., 7, 1551-1568.
31. Wang, G. et al. (2005) WordSpy: identifying transcription factor binding motifs by building a dictionary and learning a grammar. Nucleic Acids Res., 33, W412-W416.
32. Weirauch, M.T. et al. (2013) Evaluation of methods for modeling transcription factor sequence specificity. Nat. Biotechnol., 31, 126-134.