Korn LJ, Queen CL, Wegman MN: Computer analysis of nucleic acid regulatory sequences. Proc Natl Acad Sci U S A 1977,74(10):4401-5.
PubMed
CAS
PubMed Central
Google Scholar
Queen C, Wegman MN, Korn LJ: Improvements to a program for DNA analysis: a procedure to find homologies among many sequences. Nucleic Acids Res 1982, 10: 449-56.
PubMed
CAS
PubMed Central
Google Scholar
Stormo GD, Schneider TD, Gold L, Ehrenfeucht A: of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli. Nucleic Acids Res 1982,10(9):2997-3011.
PubMed
CAS
PubMed Central
Google Scholar
Staden R: Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res 1984,12(1 Pt 2):505-19.
PubMed
CAS
PubMed Central
Google Scholar
Stormo GD: DNA binding sites: representation and discovery. Bioinformatics 2000, 16: 16-23.
PubMed
CAS
Google Scholar
Pavesi G, Mauri G, Pesole G: In silico representation and discovery of transcription factor binding sites. Brief Bioinform 2004,5(3):217-36.
PubMed
CAS
Google Scholar
Wasserman WW, Krivan W: In silico identification of metazoan transcriptional regulatory regions. Naturwissenschaften 2003,90(4):156-66.
PubMed
CAS
Google Scholar
Bulyk ML: Computational prediction of transcription-factor binding site locations. Genome Biol 2003, 5: 201.
PubMed
PubMed Central
Google Scholar
Hannenhalli S, Levy S: Promoter prediction in the human genome. Bioinformatics 2001,17(Suppl 1):S90-6.
PubMed
Google Scholar
Tompa M, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV, Frith MC, Fu Y, Kent WJ, Makeev VJ, Mironov AA, Noble WS, Pavesi G, Pesole G, Regnier M, Simonis N, Sinha S, Thijs G, van Helden J, Vandenbogaert M, Weng Z, Workman C, Ye C, Zhu Z: Assessing computational tools for the discovery of transcription factor binding sites. Nat Biotechnol 2005, 23: 137-44.
PubMed
CAS
Google Scholar
van Driel R, Fransz PF, Verschure PJ: The eukaryotic genome: a system regulated at different hierarchical levels. J Cell Sci 2003,116(Pt 20):4067-75.
PubMed
CAS
Google Scholar
Werner T: Models for prediction and recognition of eukaryotic promoters. Mamm Genome 1999,10(2):168-75.
PubMed
CAS
Google Scholar
Wray GA, Hahn MW, Abouheif E, Balhoff JP, Pizer M, Rockman MV, Romano LA: The evolution of transcriptional regulation in eukaryotes. Mol Biol Evol 2003,20(9):1377-419.
PubMed
CAS
Google Scholar
Pedersen AG, Baldi P, Chauvin Y, Brunak S: The biology of eukaryotic promoter prediction–areview. Comput Chem 1999,23(3–4):191-207.
PubMed
CAS
Google Scholar
Kato M, Hata N, Banerjee N, Futcher B, Zhang MQ: Identifying combinatorial regulation of transcription factors and binding motifs. Genome Biol 2004,5(8):R56.
PubMed
PubMed Central
Google Scholar
Brazma A, Jonassen I, Eidhammer I, Gilbert D: Approaches to the automatic discovery of patterns in biosequences. J Comput Biol 1998,5(2):279-305.
PubMed
CAS
Google Scholar
Brazma A, Jonassen I, Vilo J, Ukkonen E: Pattern Discovery in Biosequences. In ICGI '98:Proceedings of the 4th International Colloquium on Grammatical Inference. London, UK: Springer-Verlag; 1998:257-270.
Google Scholar
Table of motif discovery tools[http://www.ntnu.no/~drablos/motif/discovery_tools.html]
Berg OG, von Hippel PH: Selection of DNA binding sites by regulatory proteins.Statistical-mechanical theory and application to operators and promoters. J Mol Bio l 1987,193(4):723-50.
CAS
Google Scholar
Benos PV, Bulyk ML, Stormo GD: Additivity in protein-DNA interactions: how good an approximation is it? Nucleic Acids Res 2002,30(20):4442-51.
PubMed
CAS
PubMed Central
Google Scholar
Zhou Q, Liu JS: Modeling within-motif dependence for transcription factor binding site predictions. Bioinformatics 2004,20(6):909-16.
PubMed
CAS
Google Scholar
O'Flanagan RA, Paillard G, Lavery R, Sengupta AM: Non-additivity in protein-DNA binding. Bioinformatics 2005,21(10):2254-2263.
PubMed
Google Scholar
Stormo GD, Schneider TD, Gold L: Quantitative analysis of the relationship between nucleotide sequence and functional activity. Nucleic Acids Res 1986,14(16):6661-79.
PubMed
CAS
PubMed Central
Google Scholar
Barash Y, Elidan G, Friedman N, Kaplan T: Modeling dependencies in protein-DNA binding sites. In RECOMB '03: Proceedings of the seventh annual international conference on Computational molecular biology. New York, NY, USA: ACM Press; 2003:28-37.
Google Scholar
Lim LP, Burge CB: A computational analysis of sequence features involved in recognition of short introns. Proc Natl Acad Sci USA 2001,98(20):11193-8.
PubMed
CAS
PubMed Central
Google Scholar
Cawley S: Statistical models for DNA sequencing and analysisspliceosome: motors, clocks, springs, and things. Cel 1, Statistical models for DNA sequencing and analysis. PhD thesis. University of California at Berkely, Berkely, CA; 2000.
Google Scholar
Zhao X, Huang H, Speed TP: Finding short DNA motifs using permuted markov models. In. In RECOMB '04-' Proceedings of the eighth annual international conference on Computational molecular biology. New York, NY, USA: ACM Press; 2004:68-75.
Google Scholar
Ben-Gal I, Shani A, Gohr A, Grau J, Arviv S, Shmilovici A, Posch S, Grosse I: Identification of transcription factor binding sites with variable-order Bayesian networks. Bioinformatics 2005,21(11):1367-4803.
Google Scholar
Xing EP, Jordan MI, Karp RM, Russell S: A hierarchical bayesian markovian model for motifs in biopolymer sequences. In Advances in Neural Information Processing Systems. Volume 16. Edited by: Becker S, Thrun S, Obermayer K. MIT Press, Cambridge, MA; 2002.
Google Scholar
Kechris KJ, van Zwet E, Bickel PJ, Eisen MB: Detecting DNA regulatory motifs by incorporating positional trends in information content. Genome Biol 2004,5(7):R50.
PubMed
PubMed Central
Google Scholar
van Helden J, Andre B, Collado-Vides J: Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies. J Mol Biol 1998,281(5):827-42.
PubMed
CAS
Google Scholar
Jensen LJ, Knudsen S: Automatic discovery of regulatory patterns in promoter regions based on whole cell expression data and functional annotation. Bioinformatics 2000,16(4):326-33.
PubMed
CAS
Google Scholar
Sinha S, Tompa M: A statistical method for finding transcription factor binding sites. Proc Int Conf Intell Syst Mol Biol 2000, 8: 344-54.
PubMed
CAS
Google Scholar
Bussemaker HJ, Li H, Siggia ED: Building a dictionary for genomes: identification of presumptive regulatory sites by statistical analysis. Proc Natl Acad Sci USA 2000,97(18):10096-100.
PubMed
CAS
PubMed Central
Google Scholar
van Helden J, Rios AF, Collado-Vides J: Discovering regulatory elements in non-coding sequences by analysis of spaced dyads. Nucleic Acids Res 2000,28(8):1808-18.
PubMed
CAS
Google Scholar
Shinozaki D, Maruyama O: A Method for the Best Model Selection for Single and Paired Motifs. In Genome Informatics. Volume 13. Universal Academy Press; 2002:432-433.
Google Scholar
Takusagawa KT, Gifford DK: Negative information for motif discovery. Pac Symp Biocomput 2004, 360-71.
Google Scholar
Xie X, Lu J, Kulbokas EJ, Golub TR, Mootha V, Lindblad-Toh K, Lander ES, Kellis M: Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals. Nature 2005,434(7031):338-45.
PubMed
CAS
PubMed Central
Google Scholar
Tompa M: An exact method for finding short motifs in sequences, with application to the ribosome binding site problem. In Proc Int Conf Intell Syst Mol Biol. Heidelberg, Germany; 1999:262-71.
Google Scholar
Marsan L, Sagot MF: Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory site consensus identification. J Comput Biol 2000,7(3–4):345-62.
PubMed
CAS
Google Scholar
Pevzner PA, Sze SH: Combinatorial approaches to finding subtle signals in DNA sequences. Proc Int Conf Intell Syst Mol Biol 2000, 8: 269-78.
PubMed
CAS
Google Scholar
Pavesi G, Mauri G, Pesole G: An algorithm for finding signals of unknown length in DNA sequences. Bioinformatics 2001,17(Suppl 1):S207-14.
PubMed
Google Scholar
Eskin E, Pevzner PA: Finding composite regulatory patterns in DNA sequences. Bioinformatics 2002,18(Suppl 1):S354-63.
PubMed
Google Scholar
Baldwin NE, Collins RL, Langston MA, Leuze MR, Symons CT, Voy BH: High performance computational tools for motif discovery. 18th International Parallel and Distributed Processing Symposium (IPDPS'04) – Workshop 9 2004, 192a.
Google Scholar
Li HL, Fu CJ: A linear programming approach for identifying a consensus sequence on DNA sequences. Bioinformatics 2005,21(19):1838-1845.
PubMed
CAS
Google Scholar
Blanchette M, Tompa M: Discovery of regulatory elements by a computational method for phylogenetic footprinting. Genome Res 2002,12(5):739-48.
PubMed
CAS
PubMed Central
Google Scholar
Jensen ST, Liu XS, Liu JS, Zhou Q: Computational Discovery of Gene Regulatory Binding Motifs: A Bayesian Perspective. Statist Sci 2004, 19: 188-204.
Google Scholar
Sinha S, van Nimwegen E, Siggia ED: A probabilistic method to detect regulatory modules. Bioinformatics 2003,19(Suppl 1):i292-301.
PubMed
Google Scholar
Liu X, Brutlag DL, Liu JS: BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes. Pac Symp Biocomput 2001, 127-38.
Google Scholar
Donaldson IJ, Chapman M, Gottgens B: TFBScluster: a resource for the characterisation of transcriptional regulatory networks. Bioinformatics 2005,21(13):1367-4803.
Google Scholar
McCue L, Thompson W, Carmack C, Ryan MP, Liu JS, Derbyshire V, Lawrence CE: Phylogenetic footprinting of transcription factor binding sites in proteobacterial genomes. Nucleic Acids Res 2001,29(3):774-82.
PubMed
CAS
PubMed Central
Google Scholar
Thompson W, Rouchka EC, Lawrence CE: Gibbs Recursive Sampler: finding transcription factor binding sites. Nucleic Acids Res 2003,31(13):3580-5.
PubMed
CAS
PubMed Central
Google Scholar
Tagle DA, Koop BF, Goodman M, Slightom JL, Hess DL, Jones RT: Embryonic epsilon and gamma globin genes of a prosimian primate (Galago crassicaudatus). Nucleotide and amino acid sequences, developmental regulation and phylogenetic footprints. J Mol Biol 1988,203(2):439-55.
PubMed
CAS
Google Scholar
Zhang Z, Gerstein M: Of mice and men: phylogenetic footprinting aids the discovery of regulatory elements. J Biol 2003,2(2):11.
PubMed
PubMed Central
Google Scholar
Krivan W, Wasserman WW: A predictive model for regulatory sequences directing liver-specific transcription. Genome Res 2001,11(9):1559-66.
PubMed
CAS
PubMed Central
Google Scholar
Sharan R, Ovcharenko I, Ben-Hur A, Karp RM: CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments. Bioinformatics 2003,19(Suppl 1):i283-91.
PubMed
Google Scholar
Cora D, Herrmann C, Dieterich C, Di Cunto F, Provero P, Caselle M: Ab initio identification of putative human transcription factor binding sites by comparative genomics. BMC Bioinformatics 2005, 6: 110.
PubMed
CAS
PubMed Central
Google Scholar
Wasserman WW, Fickett JW: Identification of regulatory regions which confer muscle-specific gene expression. J Mol Biol 1998, 278: 167-81.
PubMed
CAS
Google Scholar
Wang T, Stormo GD: Identifying the conserved network of cis-regulatory sites of a eukaryotic genome. Proc Natl Acad Sci USA 2005,102(48):17400-5.
PubMed
CAS
PubMed Central
Google Scholar
Beiko RG, Charlebois RL: GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA. BMC Bioinformatics 2005, 6: 36.
PubMed
PubMed Central
Google Scholar
Pudimat R, Schukat-Talamazzini EG, Backofen R: Feature Based Representation and Detection of Transcription Factor Binding Sites. Proceedings of the German Conference on Bioinformatics 2004, 43-52.
Google Scholar
Ponomarenko JV, Ponomarenko MP, Frolov AS, Vorobyev DG, Overton GC, Kolchanov NA: Conformational and physicochemical DNA features specific for transcription factor binding sites. Bioinformatics 1999,15(7–8):654-68.
PubMed
CAS
Google Scholar
El Hassan MA, Calladine CR: Conformational characteristics of DNA: empirical classifications and a hypothesis for the conformational behaviour of dinucleotide steps. Roy Soc of London Phil Tr A 1997,355(1722):43-100.
CAS
Google Scholar
Kel A, Kel-Margoulis O, Ivanova T, Wingender E: ClusterScan: A Tool for Automatic Annotation of Genomic Regulatory Sequences by Searching for Composite Clusters. Proceedings of the German Conference on Bioinformatics 2001, 96-101.
Google Scholar
Hu YJ: Finding subtle motifs with variable gaps in unaligned DNA sequences. Comput Methods Programs Biomed 2003, 70: 11-20.
PubMed
Google Scholar
Thompson W, Palumbo MJ, Wasserman WW, Liu JS, Lawrence CE: Decoding human regulatory circuits. Genome Res 2004,14(10A):1967-74.
PubMed
CAS
PubMed Central
Google Scholar
Bussemaker HJ, Li H, Siggia ED: Regulatory element detection using correlation with expression. Nat Genet 2001,27(2):167-71.
PubMed
CAS
Google Scholar
GimaThakurta D, Stormo GD: Identifying target sites for cooperatively binding factors. Bioinformatics 2001,17(7):608-21.
Google Scholar
Rebeiz M, Reeves NL, Posakony JW: SCORE: a computational approach to the identification of cis-regulatory modules and target genes in whole-genome sequence data. Site clustering over random expectation. Proc Natl Acad Sci USA 2002,99(15):9888-93.
PubMed
CAS
PubMed Central
Google Scholar
Aerts S, Van Loo P, Thijs G, Moreau Y, De Moor B: Computational detection of cis -regulatory modules. Bioinformatics 2003,19(Suppl 2):II5-II14.
PubMed
Google Scholar
Bailey TL, Noble WS: Searching for statistically significant regulatory modules. Bioinformatics 2003,19(Suppl 2):II16-II25.
PubMed
Google Scholar
Frith MC, Hansen U, Weng Z: Detection of cis-element clusters in higher eukaryotic DNA. Bioinformatics 2001,17(10):878-89.
PubMed
CAS
Google Scholar
Xing EP, Wu W, Jordan MI, Karp RM: Logos: a modular bayesian model for de novo motif detection. J Bioinform Comput Biol 2004, 2: 127-54.
PubMed
CAS
Google Scholar
Gupta M, Liu JS: De novo cis-regulatory module elicitation for eukaryotic genomes. Proc Natl Acad Sci USA 2005,102(20):7079-84.
PubMed
CAS
PubMed Central
Google Scholar
Wagner A: Genes regulated cooperatively by one or more transcription factors and their identification in whole eukaryotic genomes. Bioinformatics 1999,15(10):776-84.
PubMed
CAS
Google Scholar
Frech K, Werner T: Specific modelling of regulatory units in DNA sequences. Pac Symp Biocomput 1997, 151-62.
Google Scholar
Scherf M, Klingenhoff A, Werner T: Highly specific localization of promoter regions in large genomic sequences by Promoterlnspector: a novel context analysis approach. J Mol Biol 2000,297(3):599-606.
PubMed
CAS
Google Scholar
Brazma A, Vilo J, Ukkonen E, Valtonen K: Data mining for regulatory elements in yeast genome. Proc Int Conf Intell Syst Mol Biol 1997, 5: 65-74.
PubMed
CAS
Google Scholar
Policriti A, Vitacolonna N, Morgante M, Zuccolo A: Structured motifs search. In RECOMB '04: Proceedings of the eighth annual international conference on Computational molecular biology. New York, NY, USA: ACM Press; 2004:133-139.
Google Scholar
Berman BP, Nibu Y, Pfeiffer BD, Tomancak P, Celniker SE, Levine M, Rubin GM, Eisen MB: Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome. Proc Natl Acad Sci USA 2002,99(2):757-62.
PubMed
CAS
PubMed Central
Google Scholar
Segal E, Barash Y, Simon I, Friedman N, Koller D: From promoter sequence to expression: a probabilistic framework. In RECOMB '02: Proceedings of the sixth annual international conference on Computational biology. New York, NY, USA: ACM Press; 2002:263-272.
Google Scholar
Aerts S, Van Loo P, Moreau Y, De Moor B: A genetic algorithm for the detection of new cis-regulatory modules in sets of coregulated genes. Bioinformatics 2004,20(12):1974-6.
PubMed
CAS
Google Scholar
Klingenhoff A, Freeh K, Quandt K, Werner T: Functional promoter modules can be detected by formal models independent of overall nucleotide sequence similarity. Bioinformatics 1999,15(3):180-6.
PubMed
CAS
Google Scholar
Johansson O, Alkema W, Wasserman WW, Lagergren J: Identification of functional clusters of transcription factor binding motifs in genome sequences: the MSCAN algorithm. Bioinformatics 2003,19(Suppl 1):i169-76.
PubMed
Google Scholar
Mahony S, Hendrix D, Golden A, Smith TJ, Rokhsar DS: Transcription factor binding site identification using the self-organizing map. Bioinformatics 2005,21(9):1807-1814.
PubMed
CAS
Google Scholar
Workman CT, Stormo GD: a method for discovering transcription factor binding sites with improved specificity. Pac Symp Biocomput 2000, 467-78.
Google Scholar
Liu XS, Brutlag DL, Liu JS: An algorithm for finding protein-DNA binding sites with applications to chromatin-immunoprecipitation microarray experiments. Nat Biotechnol 2002,20(8):835-9.
PubMed
CAS
Google Scholar
Wang T, Stormo GD: Combining phylogenetic data with co-regulated genes to identify regulatory motifs. Bioinformatics 2003,19(18):2369-80.
PubMed
CAS
Google Scholar
Conlon EM, Liu XS, Lieb JD, Liu JS: Integrating regulatory motif discovery and genome-wide expression analysis. Proc Natl Acad Sci USA 2003,100(6):3339-44.
PubMed
CAS
PubMed Central
Google Scholar
Frith MC, Fu Y, Yu L, Chen JF, Hansen U, Weng Z: Detection of functional DNA motifs via statistical over-representation. Nucleic Acids Res 2004,32(4):1372-81.
PubMed
CAS
PubMed Central
Google Scholar
Caselle M, Di Cunto F, Provero P: Correlating overrepresented upstream motifs to gene expression: a computational approach to regulatory element discovery in eukaryotes. BMC Bioinformatics 2002, 3: 7.
PubMed
PubMed Central
Google Scholar
Cora D, Di Cunto F, Provero P, Silengo L, Caselle M: Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs. BMC Bioinformatics 2004, 5: 57.
PubMed
PubMed Central
Google Scholar
Curran MD, Liu H, Long F, Ge N: Statistical methods for joint data mining of gene expression and DNA sequence database. SIGKDD Explor Newsl 2003,5(2):122-129.
Google Scholar
Segal E, Yelensky R, Koller D: Genome-wide discovery of transcriptional modules from DNA sequence and gene expression. Bioinformatics 2003,19(Suppl 1):i273-82.
PubMed
Google Scholar
Hong P, Liu X, Zhou Q, Lu X, Liu JS, Wong WH: A boosting approach for motif modeling using ChlP-chip data. Bioinformatics 2005,21(11):2636-2643.
PubMed
CAS
Google Scholar
Gupta M, Liu JS: Discovery of Conserved Sequence Patterns Using a Stochastic Dictionary Model. Journal of the American Statistical Association 2003, 98: 55-66.
Google Scholar
Lawrence CE, Altschul SF, Boguski MS, Liu JS, Neuwald AF, Wootton JC: Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 1993,262(5131):208-14.
PubMed
CAS
Google Scholar
Bailey TL, Elkan C: The value of prior knowledge in discovering motifs with. Proc Int Conf Intell Syst Mol Biol 1995, 3: 21-9.
PubMed
CAS
Google Scholar
Jonassen I: Efficient discovery of conserved patterns using a pattern graph. Comput ApplBiosci 1997,13(5):509-22.
CAS
Google Scholar
Rigoutsos I, Floratos A: Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm. Bioinformatics 1998, 14: 55-67.
PubMed
CAS
Google Scholar
Rustici G, Mata J, Kivinen K, Lio P, Penkett CJ, Burns G, Hayles J, Brazma A, Nurse P, Bahler J: Periodic gene expression program of the fission yeast cell cycle. Nat Genet 2004,36(8):809-17.
PubMed
CAS
Google Scholar
Birnbaum K, Benfey PN, Shasha DE: cis element/transcription factor analysis (cis/TF): a method for discovering transcription factor/cis element relationships. Genome Res 2001,11(9):1567-73.
PubMed
CAS
PubMed Central
Google Scholar
Zhu Z, Pilpel Y, Church GM: Computational identification of transcription factor binding sites via a transcription-factor-centric clustering (TFCC) algorithm. J Mol Biol 2002, 318: 71-81.
PubMed
CAS
Google Scholar
Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N, Kanin E, Volkert TL, Wilson CJ, Bell SP, Young RA: Genome-wide location and function of DNA binding proteins. Science 2000,290(5500):2306-9.
PubMed
CAS
Google Scholar
Buck MJ, Lieb JD: ChlP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments. Genomics 2004,83(3):349-60.
PubMed
CAS
Google Scholar
Mironov AA, Koonin EV, Roytberg MA, Gelfand MS: Computer analysis of transcription regulatory patterns in completely sequenced bacterial genomes. Nucleic Acids Res 1999,27(14):2981-9.
PubMed
CAS
PubMed Central
Google Scholar
Qin ZS, McCue LA, Thompson W, Mayerhofer L, Lawrence CE, Liu JS: Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites. Nat Biotechnol 2003,21(4):435-9.
PubMed
CAS
Google Scholar
McGuire AM, Hughes JD, Church GM: Conservation of DNA regulatory motifs and discovery of new motifs in microbial genomes. Genome Res 2000,10(6):744-57.
PubMed
CAS
Google Scholar
Thijs G, Marchal K, Lescot M, Rombauts S, De Moor B, Rouze P, Moreau Y: A Gibbs sampling method to detect overrepresented motifs in the upstream regions of coexpressed genes. J Comput Biol 2002,9(2):447-64.
PubMed
CAS
Google Scholar
Park PJ, Butte AJ, Kohane IS: Comparing expression profiles of genes with similar promoter regions. Bioinformatics 2002,18(12):1576-84.
PubMed
CAS
Google Scholar
Holmes I, Bruno WJ: Finding regulatory elements using joint likelihoods for sequence and expression profile data. Proc Int Conf Intell Syst Mol Biol 2000, 8: 202-10.
PubMed
CAS
Google Scholar
Bar-Joseph Z, Gerber GK, Lee TI, Rinaldi NJ, Yoo JY, Robert F, Gordon DB, Fraenkel E, Jaakkola TS, Young RA, Gifford DK: Computational discovery of gene modules and regulatory networks. Nat Biotechnol 2003,21(11):1337-42.
PubMed
CAS
Google Scholar
Evans PA, Smith AD: Toward optimal motif enumeration. In Proceedings of Workshop on Algorithms and Data Structures (WADS 2003). Volume 2751. Springer-Verlag; 2003:47-58.
Google Scholar
Lawrence CE, Reilly AA: An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences. Proteins 1990, 7: 41-51.
PubMed
CAS
Google Scholar
Sinha S, Blanchette M, Tompa M: PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences. BMC Bioinformatics 2004, 5: 170.
PubMed
PubMed Central
Google Scholar
Prakash A, Blanchette M, Sinha S, Tompa M: Motif discovery in heterogeneous sequence data. Pac Symp Biocomput 2004, 348-59.
Google Scholar
Ao W, Gaudet J, Kent WJ, Muttumu S, Mango SE: Environmentally induced foregut remodeling by PHA-4/FoxA and DAF-12/NHR. Science 2004,305(5691):1743-6.
PubMed
CAS
Google Scholar
Neuwald AF, Liu JS, Lawrence CE: Gibbs motif sampling: detection of bacterial outer membrane protein repeats. Protein Sci 1995,4(8):1618-32.
PubMed
CAS
PubMed Central
Google Scholar
Zhou Q, Wong WH: CisModule: de novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proc Natl Acad Sci USA 2004,101(33):12114-9.
PubMed
CAS
PubMed Central
Google Scholar
Grad YH, Roth FP, Halfon MS, Church GM: Prediction of similarly-acting cis-regulatory modules by subsequence profiling and comparative genomics in D. melanogaster and D. pseudoobscura. Bioinformatics 2004,20(16):2738-2750.
PubMed
CAS
Google Scholar
Hart RK, Royyuru AK, Stolovitzky G, Califano A: Systematic and fully automated identification of protein sequence patterns. J Comput Biol 2000,7(3–4):585-600.
PubMed
CAS
Google Scholar
Favorov AV, Gelfand MS, Gerasimova AV, Ravcheev DA, Mironov AA, Makeev VJ: A Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length. Bioinformatics 2005,21(10):2240-2245.
PubMed
CAS
Google Scholar
Marsan L, Sagot MF: Extracting structured motifs using a suffix treealgorithms and application to promoter consensus identification. In RECOMB '00: Proceedings of the fourth annual international conference on Computational molecular biology. New York, NY, USA: ACM Press; 2000:210-219.
Google Scholar
Roth FP, Hughes JD, Estep PW, Church GM: Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation. Nat Biotechnol 1998,16(10):939-45.
PubMed
CAS
Google Scholar