Comparative Analysis of Regulatory Motif Discovery Tools for Transcription Factor Binding Sites

Genomics, Proteomics and Bioinformatics

Volumn 5, Issue 2, 2007, Pages 131-142

  Wei, Wei ^a   Yu, Xiao Dan ^a  

^a INSTITUTE OF BASIC MEDICAL SCIENCES   (China)

Author keywords

computational algorithm; motif; motif discovery tool; non coding DNA sequence; TFBS

Indexed keywords

TRANSCRIPTION FACTOR;

ACCURACY; ALGORITHM; ARTICLE; BINDING SITE; COMBINATORIAL LIBRARY; COMPARATIVE STUDY; DATA BASE; DNA SEQUENCE; GENOMICS; PROTEIN MOTIF; TRANSCRIPTION REGULATION;

ALGORITHMS; AMINO ACID MOTIFS; BASE SEQUENCE; BINDING SITES; COMPUTATIONAL BIOLOGY; INTERNET; MOLECULAR SEQUENCE DATA; PROTEIN BINDING; REGULATORY ELEMENTS, TRANSCRIPTIONAL; SEQUENCE ANALYSIS, DNA; SEQUENCE HOMOLOGY, NUCLEIC ACID; TRANSCRIPTION FACTORS;

EID: 34548761859     PISSN: 16720229     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1672-0229(07)60023-0     Document Type: Article

References (113)

1. Roulet E., et al. High-throughput SELEX-SAGE method for quantitative modeling of transcription-factor binding sites. Nat. Biotechnol. 20 (2002) 831-835
2. van Steensel B. Mapping of genetic and epigenetic regulatory networks using microarrays. Nat. Genet. 37 (2005) S18-S24
3. Cam H., et al. A common set of gene regulatory networks links metabolism and growth inhibition. Mol. Cell 16 (2004) 399-411
4. Blais A., and Dynlacht B.D. Constructing transcriptional regulatory networks. Genes Dev. 19 (2005) 1499-1511
5. Wasserman W.W., and Sandelin A. Applied bioinformatics for the identification of regulatory elements. Nat. Rev. Genet. 5 (2004) 276-287
6. Vavouri T., and Elgar G. Prediction of cisregulatory elements using binding site matrices-the successes, the failures and the reasons for both. Curr. Opin. Genet. Dev. 15 (2005) 395-402
7. Staden R. Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res. 12 (1984) 505-519
8. Schneider T.D., and Stephens R.M. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res. 18 (1990) 6097-6100
9. King M.C., and Wilson A.C. Evolutions at two levels in humans and chimpanzees. Science 188 (1975) 107-116
10. Cawley S., et al. Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 116 (2004) 499-509
11. Impey S., et al. Defining the CREB regulon: a genome-wide analysis of transcription factor regulatory regions. Cell 119 (2004) 1041-1054
12. Tompa M., et al. Assessing computational tools for the discovery of transcription factor binding sites. Nat. Biotechnol. 23 (2005) 137-144
13. Kirchhamer C.V., et al. Modular cis-regulatory organization of developmentally expressed genes: two genes transcribed territorially in the sea urchin embryo, and additional examples. Proc. Natl. Acad. Sci. USA 93 (1996) 9322-9328
14. Pennacchio L.A., and Rubin E.M. Genomic strategies to identify mammalian regulatory sequences. Nat. Rev. Genet. 2 (2001) 100-109
15. van Helden J., et al. Discovering regulatory elements in non-coding sequences by analysis of spaced dyads. Nucleic Acids Res. 28 (2000) 1808-1818
16. Brazma A., et al. Predicting gene regulatory elements in silico on a genomic scale. Genome Res. 8 (1998) 1202-1215
17. Eskin E., et al. Finding composite regulatory patterns in DNA sequences. Bioinformatics 18 (2002) S354-S363
18. Klingenhoff A., et al. Functional promoter modules can be detected by formal models independent of overall nucleotide sequence similarity. Bioinformatics 15 (1999) 180-186
19. Gusfield D. Algorithms on Strings, Trees and Sequences (1997), Cambridge University Press, Cambridge, UK
20. Ohler U., and Niemann H. Identification and analysis of eukaryotic promoters: recent computational approaches. Trends Genet. 17 (2001) 56-60
21. Keich U., and Pevzner P.A. Subtle motifs: defining the limits of motif finding algorithms. Bioinformatics 18 (2002) 1382-1390
22. Kravchenko J.E., et al. Transcription of mammalian messenger RNAs by a nuclear RNA polymerase of mitochondrial origin. Nature 436 (2005) 735-739
23. Stormo G.D., and Hartzell III G.W. Identifying protein-binding sites from unaligned DNA fragments. Proc. Natl. Acad. Sci. USA 86 (1989) 1183-1187
24. Hertz G.Z., and Stormo G.D. Identifying DNA and protein patterns with statistically significant alignments of multiple sequences. Bioinformatics 15 (1999) 563-577
25. Lenz D.H., et al. The small RNA chaperone Hfq and multiple small RNAs control quorum sensing in Vibrio harveyi and Vibrio cholerae. Cell 118 (2004) 69-82
26. Fung M.M., et al. IL-2-and STAT5-regulated cytokine gene expression in cells expressing the Tax protein of HTLV-1. Oncogene 24 (2005) 4624-4633
27. Rigoutsos I., and Floratos A. Combinatorial pattern discovery in biological sequences: the TEIRESIAS algorithm. Bioinformatics 14 (1998) 55-67
28. Jensen K.L., et al. A generic motif discovery algorithm for sequential data. Bioinformatics 22 (2006) 2128
29. Kiesler E., et al. Hrp59, an hnRNP M protein in Chironomus and Drosophila, binds to exonic splicing enhancers and is required for expression of a subset of mRNAs. J. Cell Biol. 168 (2005) 1013-1025
30. Pevzner P.A., and Sze S.H. Combinatorial approaches to finding subtle signals in DNA sequences. Proc. Int. Conf. Intell. Syst. Mol. Biol. 8 (2000) 269-278
31. Liang S., et al. cWINNOWER algorithm for finding fuzzy DNA motifs. J. Bioinform. Comput. Biol. 2 (2004) 47-60
32. Bussemaker H.J., et al. Building a dictionary for genomes: identification of presumptive regulatory sites by statistical analysis. Proc. Natl. Acad. Sci. USA 97 (2000) 10096-10100
33. Murphy C.T., et al. Genes that act downstream of DAF-16 to influence the lifespan of Caenorhabditis elegans. Nature 424 (2003) 277-283
34. Marsan L., and Sagot M.F. Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory site consensus identification. J. Comput. Biol. 7 (2000) 345-362
35. Apostolico A., et al. Verbumculus and the discovery of unusual words. J. Comput. Sci. Technol. 19 (2004) 22-41
36. Pavesi G., et al. An algorithm for finding signals of unknown length in DNA sequences. Bioinformatics 17 (2001) S207-S214
37. Eskin E., and Pevzner P.A. Finding composite regulatory patterns in DNA sequences. Bioinformatics 18 (2002) S354-S363
38. Buhler J., and Tompa M. Finding motifs using random projections. J. Comput. Biol. 9 (2002) 225-242
39. Fogel G.B., et al. Discovery of sequence motifs related to coexpression of genes using evolutionary computation. Nucleic Acids Res. 32 (2004) 3826-3835
40. Gertz J., et al. Discovery, validation, and genetic dissection of transcription factor binding sites by comparative and functional genomics. Genome Res. 15 (2005) 1145-1152
41. Hernandez D., et al. MoDEL: an efficient strategy for ungapped local multiple alignment. Comput. Biol. Chem. 28 (2004) 119-128
42. Sinha S., et al. A probabilistic method to detect regulatory modules. Bioinformatics 19 (2003) i292-i301
43. Moon T.K. The expectation-maximization algorithm. IEEE Signal Proc. Mag. 13 (1996) 47-60
44. Lawrence C.E., et al. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 262 (1993) 208-214
45. Petersen M., et al. Arabidopsis MAP kinase 4 negatively regulates systemic acquired resistance. Cell 103 (2000) 1111-1120
46. Bailey T.L., and Gribskov M. Methods and statistics for combining motif match scores. J. Comput. Biol. 5 (1998) 211-221
47. Hall N., et al. A comprehensive survey of the Plasmodium life cycle by genomic, transcriptomic, and proteomic analyses. Science 307 (2005) 82-86
48. Xing E.P., et al. LOGOS: a modular Bayesian model for de novo motif detection. J. Bioinform. Comput. Biol. 2 (2004) 127-154
49. Xing E.P., and Karp R.M. MotifPrototyper: a Bayesian profile model for motif families. Proc. Natl. Acad. Sci. USA 101 (2004) 10523-10528
50. Thijs G., et al. A higher-order background model improves the detection of regulatory elements by Gibbs sampling. Bioinformatics 17 (2001) 1113-1122
51. Le Crom S., et al. New insights into the pleiotropic drug resistance network from genome-wide characterization of the YRR1 transcription factor regulation system. Mol. Cell. Biol. 22 (2002) 2642-2649
52. Roth F.P., et al. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation. Nat. Biotechnol. 16 (1998) 939-945
53. Wade J.T., et al. The transcription factor Ifh1 is a key regulator of yeast ribosomal protein genes. Nature 432 (2004) 1054-1058
54. Wade J.T., et al. Genomic analysis of LexA binding reveals the permissive nature of the Escherichia coli genome and identifies unconventional target sites. Genes Dev. 19 (2005) 2619-2630
55. Workman C.T., and Stormo G.D. ANN-Spec: a method for discovering transcription factor binding sites with improved specificity. Pac. Symp. Biocomput. (2000) 467-478
56. GuhaThakurta D., et al. Identification of a novel cis-regulatory element involved in the heat shock response in Caenorhabditis elegans using microarray gene expression and computational methods. Genome Res. 12 (2002) 701-712
57. Liu X., et al. BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes. Pac. Symp. Biocomput. (2001) 127-138
58. Mukherjee S., et al. Rapid analysis of the DNAbinding specificities of transcription factors with DNA microarrays. Nat. Genet. 36 (2004) 1331-1339
59. Liu X.S., et al. An algorithm for finding protein-DNA binding sites with applications to chromatin immunoprecipitation microarray experiments. Nat. Biotechnol. 20 (2002) 835-839
60. Carroll J.S., et al. Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1. Cell 122 (2005) 33-43
61. Ben Y.S., et al. Defining a centromere-like element in Bacillus subtilis by identifying the binding sites for the chromosome-anchoring protein RacA. Mol. Cell 17 (2005) 773-782
62. Ao W., et al. Environmentally induced foregut remodeling by PHA-4/FoxA and DAF-12/NHR. Science 305 (2004) 1743-1746
63. Favorov A.V., et al. A Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length. Bioinformatics 21 (2005) 2240-2245
64. Zhou Q., and Liu J.S. Modeling within-motif dependence for transcription factor binding site predictions. Bioinformatics 20 (2004) 909-916
65. Blanchette M., et al. Algorithms for phylogenetic footprinting. J. Comput. Biol. 9 (2002) 211-223
66. Wang T., and Stormo G.D. Combining phylogenetic data with co-regulated genes to identify regulatory motifs. Bioinformatics 19 (2003) 2369-2380
67. Hu Y., et al. RNA interference of achaete-scute homolog 1 in mouse prostate neuroendocrine cells reveals its gene targets and DNA binding sites. Proc. Natl. Acad. Sci. USA 101 (2004) 5559-5564
68. Moses A.M., et al. Phylogenetic motif detection by expectation-maximization on evolutionary mixtures. Pac. Symp. Biocomput. (2004) 324-335
69. Prakash A., et al. Motif discovery in heterogeneous sequence data. Pac. Symp. Biocomput. (2004) 348-359
70. Sinha S., et al. PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences. BMC Bioinformatics 5 (2004) 170
71. Blanchette M., and Tompa M. FootPrinter: a program designed for phylogenetic footprinting. Nucleic Acids Res. 31 (2003) 3840-3842
72. Jensen S.T., and Liu J.S. BioOptimizer: a Bayesian scoring function approach to motif discovery. Bioinformatics 20 (2004) 1557-1564
73. Ruan J., and Zhang W. CAGER: classification analysis of gene expression regulation using multiple information sources. BMC Bioinformatics 6 (2005) 114
74. Berman B.P., et al. Exploiting transcription factor binding site clustering to identify cisregulatory modules involved in pattern formation in the Drosophila genome. Proc. Natl. Acad. Sci. USA 99 (2002) 757-762
75. Zhou Q., and Wong W.H. CisModule: de novo discovery of cis-regulatory modules by hierarchical mixture modeling. Proc. Natl. Acad. Sci. USA 101 (2004) 12114-12119
76. Frith M.C., et al. Detection of cis-element clusters in higher eukaryotic DNA. Bioinformatics 17 (2001) 878-889
77. Frith M.C., et al. Detection of functional DNA motifs via statistical over-representation. Nucleic Acids Res. 32 (2004) 1372-1381
78. Kel-Margoulis O.V., et al. Automatic annotation of genomic regulatory sequences by searching for composite clusters. Pac. Symp. Biocomput. (2002) 187-198
79. GuhaThakurta D., and Stormo G.D. Identifying target sites for cooperatively binding factors. Bioinformatics 17 (2001) 608-621
80. Frith M.C., et al. Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences. Nucleic Acids Res. 30 (2002) 3214-3224
81. Sharan R., et al. CREME: a framework for identifying cis-regulatory modules in human-mouse conserved segments. Bioinformatics 19 (2003) i283-i291
82. Sandelin A., et al. ConSite: web-based prediction of regulatory elements using cross-species comparison. Nucleic Acids Res. 32 (2004) W249-W252
83. Bortoluzzi S., et al. A multistep bioinformatic approach detects putative regulatory elements in gene promoters. BMC Bioinformatics 6 (2005) 121
84. Sinha S. Discriminative motifs. J. Comput. Biol. 10 (2003) 599-615
85. Hu Y.J., et al. Combinatorial motif analysis and hypothesis generation on a genomic scale. Bioinformatics 16 (2000) 222-232
86. Cartharius K., et al. MatInspector and beyond: promoter analysis based on transcription factor binding sites. Bioinformatics 21 (2005) 2933-2942
87. Beiko R.G., and Charlebois R.L. GANN: genetic algorithm neural networks for the detection of conserved combinations of features in DNA. BMC Bioinformatics 6 (2005) 36
88. Thompson W., et al. Gibbs Recursive Sampler: finding transcription factor binding sites. Nucleic Acids Res. 31 (2003) 3580-3585
89. Frith M.C., et al. Finding functional sequence elements by multiple local alignment. Nucleic Acids Res. 32 (2004) 189-200
90. Xing E.P., et al. A hierarchical Bayesian Markovian model for motifs in biopolymer sequences. In: Becher S., et al. (Ed). Advances in Neural Information Processing Systems Vol. 16 (2002), MIT Press, Cambridge, USA
91. Marinescu V.D., et al. MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes. BMC Bioinformatics 6 (2005) 79
92. Bailey T.L., and Noble W.S. Searching for statistically significant regulatory modules. Bioinformatics 19 (2003) ii16-ii25
93. Hu Y.J. Finding subtle motifs with variable gaps in unaligned DNA sequences. Comput. Methods Programs Biomed. 70 (2003) 11-20
94. Sun Z., et al. MISAE: a new approach for regulatory motif extraction. Proc. IEEE Comput. Syst. Bioinform. Conf. (2004) 173-181
95. Leung H.C., and Chin F.Y. Finding exact optimal motifs in matrix representation by partitioning. Bioinformatics 21 (2005) ii86-ii92
96. Bailey T.L., and Elkan C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proc. Int. Conf. Intell. Syst. Mol. Biol. 2 (1994) 28-36
97. Frech K., and Werner T. Specific modelling of regulatory units in DNA sequences. Pac. Symp. Biocomput. (1997) 151-162
98. Aerts S., et al. Computational detection of cis-regulatory modules. Bioinformatics 19 (2003) ii5-ii14
99. Alkema W.B., et al. MSCAN: identification of functional clusters of transcription factor binding sites. Nucleic Acids Res. 32 (2004) W195-W198
100. Down T.A., and Hubbard T.J. NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequence. Nucleic Acids Res. 33 (2005) 1445-1453
101. King O.D., and Roth F.P. A non-parametric model for transcription factor binding sites. Nucleic Acids Res. 31 (2003) e116
102. van Helden J., et al. Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies. J. Mol. Biol. 281 (1998) 827-842
103. Narasimhan C., et al. Background rarenessbased iterative multiple sequence alignment algorithm for regulatory element detection. Bioinformatics 19 (2003) 1952-1963
104. Jonassen I. Efficient discovery of conserved patterns using a pattern graph. Comput. Appl. Biosci. 13 (1997) 509-522
105. Pudimat R., et al. A multiple-feature framework for modelling and predicting transcription factor binding sites. Bioinformatics 21 (2005) 3082-3088
106. Scherf M., et al. Highly specific localization of promoter regions in large genomic sequences by PromoterInspector: a novel context analysis approach. J. Mol. Biol. 297 (2000) 599-606
107. Boeva V., et al. Short fuzzy tandem repeats in genomic sequences, identification, and possible role in regulation of gene expression. Bioinformatics 22 (2006) 676-684
108. Bussemaker H.J., et al. Regulatory element detection using correlation with expression. Nat. Genet. 27 (2001) 167-171
109. Rebeiz M., et al. 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 99 (2002) 9888-9893
110. Mahony S., et al. Transcription factor binding site identification using the self-organizing map. Bioinformatics 21 (2005) 1807-1814
111. Hart R.K., et al. Systematic and fully automated identification of protein sequence patterns. J. Comput. Biol. 7 (2000) 585-600
112. Donaldson I.J., et al. TFBScluster: a resource for the characterization of transcriptional regulatory networks. Bioinformatics 21 (2005) 3058-3059
113. Sinha S., and Tompa M. YMF: a program for discovery of novel transcription factor binding sites by statistical overrepresentation. Nucleic Acids Res. 31 (2003) 3586-3588