Promoter sequences and algorithmical methods for identifying them

Research in Microbiology

Volumn 150, Issue 9-10, 1999, Pages 779-799

  Vanet, Anne ^a,b   Marsan, Laurent ^c   Sagot, Marie France ^b  

^a INST DE BIOLOGIE PHYSICO CHIMIQUE   (France)

^b INSTITUT PASTEUR   (France)

^c Université de Marne la Vallée   (France)

Author keywords

Algorithm; Motif extraction; Motif searching; Prokaryotes; Promoter

Indexed keywords

ALGORITHM; BACTERIAL GENETICS; MATHEMATICAL MODEL; NONHUMAN; PRIORITY JOURNAL; PROMOTER REGION; REVIEW; SEQUENCE ANALYSIS;

BACTERIA (MICROORGANISMS); EUKARYOTA; PROKARYOTA;

EID: 0033379116     PISSN: 09232508     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0923-2508(99)00115-1     Document Type: Article

References (128)

1. Ambrose C., Bina M. Strategy for statistical-mapping of potential regulatory regions in the human genome. J. Mol. Biol. 216:1990;485-490.
2. Bailey T.L. Discovering motifs in DNA and protein sequences. The approximate common substring problem. Ph.D. thesis. 1995;University of California, San Diego, USA.
3. Bailey T.L., Elkan C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. in: Second International Symposium on Intelligent Systems for Molecular Biology. 1994;28-36 Stanford University, Stanford, CA, USA.
4. Bailey T.L., Elkan C. Unsupervised learning of multiple motifs in biopolymers using EM. Machine Learn. 21:1995;51-80.
5. Bailey T.L., Elkan C. ParaMEME a parallel implementation and a web interface for a DNA and protein motif discovery tool. Comput. Appl. Biosci. 12:1996;303-310.
6. Baldi P., Chauvin Y., Hunkapiller T., McClure M.A. Hidden Markov models of biological primary sequence information. Proc. Natl. Acad. Sci. USA. 91:1994;1059-1063.
7. Benham C.J. Computation of DNA structural variability - a new predictor of DNA regulatory regions. Comput. Appl. Biosci. 12:1996;375-381.
8. Berg O.G., VonHippel P.H. Selection of DNA binding sites by regulatory proteins. I. Statistical-mechanical theory and application to operators and promoters. J. Mol. Biol. 193:1987;723-750.
9. Berg O.G., VonHippel P.H. Selection of DNA binding sites by regulatory proteins. II. The binding specificity of cyclic AMP receptor protein to recognition sites. J. Mol. Biol. 200:1988;709-723.
10. Brazma A., Jonassen I., Eidhammer I., Gilbert D. Approaches to the automatic discovery of patterns in biosequences. J. Comp. Biol. 5:1998;279-305.
11. Brazma A., Jonassen I., Vilo J., Ukkonen E. Gata mining for regulatory elements in yeast genome. Gaasterland T, Karp P, Karplus K, Ouzounis C, Sander C, Valencia A. Fifth International Symposium on Intelligent Systems for Molecular Biology. 1997;65-74 AAAI Press, Halkidiki, Greece.
12. Brazma A., Jonassen I., Vilo J., Ukkonen E. Discovering patterns and subfamilies in biosequences. in: Fourth International Symposium on Intelligent Systems for Molecular Biology. 1998;34-43 AAAI Press, Montréal, Canada.
13. Brazma A., Jonassen I., Vilo J., Ukkonen E. Pattern discovery in biosequences. Lecture Notes in Artificial Intelligence (volume 1433). 1998;255-270 Springer and Verlag.
14. Brazma A., Jonassen I., Vilo J., Ukkonen E. Predicting gene regulatory elements in silico on a genomic scale. Genome Research. 8:1998;1202-1215.
15. Bruckner I., Sánchez R., Suck S., Pongor S. Sequence-dependent bending propensity of DNA as revealed by DNase I parameters for trinucleotides. EMBO J. 14:1995;1812-1818.
16. Bucher P. Weight matrix descriptions of four eukaryotic RNA polymerase II promoter elements derived from 502 unrelated promoter sequences. J. Mol. Biol. 212:1990;563-578.
17. Bucher P. Regulatory elements and expression profiles. Curr. Opin. Struct. Biol. 9:1999;400-407.
18. Bucher P., Bryan B. Signal search analysis a new method to localize and characterize functionally important DNA sequences. Nucleic Acids Res. 12:1984;287-305.
19. Bucher P., Fickett J.W., Hatzigeorgiou A. Computational analysis of transcriptional regulatory elements a field in flux. Comput. Appl. Biosci. 12:1996;361-362.
20. Burge C. Identification of genes in human genomic DNA. Ph.D. thesis. 1997;Stanford University, Stanford, California, USA.
21. Burge C. Modeling dependencies in pre-mRNA splicing signals. Salzberg S, Searls D, Kasif S. Computational Methods in Molecular Biology. 1998;127-163 Elsevier Science, Amsterdam.
22. Burge C., Karlin S. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268:1997;78-94.
23. Calladine C.R., Drew H.R., McCall M.J. The intrinsic structure of DNA in solution. J. Mol. Biol. 201:1988;127-137.
24. Cardon L.R., Stormo G.D. Expectation Maximization algorithm for identifying protein-binding sites with variable lengths from unaligned DNA fragments. J. Mol. Biol. 223:1992;139-170.
25. Chen Q.K., Hertz G.Z., Stormo G. MATRIX SEARCH 1.0 a computer program that scans DNA sequences for transcriptional elements using a database of weight matrices. Comput. Appl. Biosci. 11:1995;563-566.
26. Combrugghe B., Busby S., Buc H. Cyclic AMP receptor protein role in transcription activation. Science. 224:1984;831-838.
27. Crochemore M., Rytter W. Text algorithms. 1994;Oxford University Press, Oxford.
28. Crowley E.M., Roeder K., Bina K.M. A statistical model for locating regulatory regions in genomic DNA. J. Mol. Biol. 268:1997;8-14.
29. Demeler B., Zhou G.W. Neural network optimization for E. coli promoter prediction. Nucleic Acids Res. 19:1991;1593-1599.
30. Dlakic M., Harrington R.E. DIAMOD display and modeling of DNA bending. Comput. Appl. Biosci. 14:1998;326-331.
31. Durbin R., Eddy S.R., Krogh A., Mitchison G. Biological sequence analysis. Probabilistic models of proteins and nucleic acids. 1998;Cambridge University Press.
32. Duret L., Bucher P. Searching for regulatory elements in human noncoding sequences. Curr. Opin. Struct. Biol. 7:1997;399-406.
33. Fickett J.W., Hatzigeorgiou A.G. Eukaryotic promoter recognition. Genome Research. 7:1997;861-878.
34. Fraenkel Y.M., Mandel Y., Friedberg D., Margalit H. Identification of common motifs in unaligned DNA sequences application to Escherichia coli lrp regulon. Comput. Appl. Biosci. 11:1995;379-387.
35. Frech K., Herrmann G., Werner T. Computer-assisted prediction classification and delimitation of protein binding sites in nucleic acids. Nucleic Acids Res. 21:1993;1655-1664.
36. Frech K., Quandt K., Werner T. Software for the analysis of DNA sequence elements of transcription. Comput. Appl. Biosci. 13:1993;89-97.
37. Galas D.J., Eggert M., Waterman M.S. Rigorous pattern-recognition methods for DNA sequences. Analysis of promoter sequences from Escherichia coli. J. Mol. Biol. 186:1985;117-128.
38. Goodsell D.S., Dickerson R.E. Bending and curvature calculations in B-DNA. Nucleic Acids Res. 22:1994;5497-5503.
39. Gusfield D. Algorithms on Strings Trees and Sequences Computer Science and Computational Biology. 1997;Cambridge University Press.
40. Harley C.B., Reynolds R.P. Amalysis of E. coli promoter sequences. Nucleic Acids Res. 15:1987;2343-2361.
41. Hawley D.K., McClure W.R. Compilation and analysis of Escherichia coli promoter DNA sequences. Nucleic Acids Res. 11:1983;2237-2255.
42. Helmann J.D. Compilation and analysis of Bacillus subtilis a-dependent promoter sequences evidence for extended contact between RNA polymerase and upstream promoter DNA. Nucleic Acids Res. 23:1995;2351-2360.
43. Hertz G.Z., Stormo G.D. Identification of consensus patterns in unaligned DNA and protein sequences A large-deviation statistical basis for penalizing gaps. Lim H.A, Cantor C.R. The third International Conference on Bioinformatics and Genome Research. 1994;201-216 World Scientific Publishing.
44. Hertz G.Z., Stormo G.D. Escherichia coli promoter sequences. Analysis and prediction. Meth. Enzymol. 273:1996;30-42.
45. Horton P.B., Kanehisa M. An assessment of neural network and statistical approaches for prediction of E. coli promoter sites. Nucleic Acids Res. 20:1992;4331-4338.
46. Hutchinson A. Algorithmic learning. 1994;Clarendon Press.
47. Ioshikhes I., Trifonov E.N., Zhang M.Q. Periodical distribution of transcription factor sites in promoter regions and connection with chromatin structure. Proc. Natl. Acad. Sci. USA. 96:1999;2891-2895.
48. Jonassen I. Efficient discovery of conserved patterns using a pattern graph. Comput. Appl. Biosci. 13:1997;509-522.
49. Jonassen I., Collins J.F., Higgins D.G. Finding flexible patterns in unaligned protein sequences, Protein. Science. 4:1995;1587-1595.
50. Karas H., Knüppel R., Schulz W., Sklenar H., Wingender E. Combining structural analysis of DNA with routines for the detection of transcription regulatory elements. Comput. Appl. Biosci. 12:1996;441-446.
51. Karlin S., Brendel V. Chance and statistical significance in protein and DNA sequence analysis. Science. 257:1992;39-49.
52. Karlin S., Bucher P., Brendel V., Altschul S.F. Statistical methods and insights for protein and DNA sequences. Annu. Rev. Biophys. Biophys. Chem. 20:1991;175-203.
53. Karlin S., Cardon L.R. Computational DNA sequence analysis. Annu. Rev. Microbiol. 48:1994;619-654.
54. Karlin S., Ghandour G. Comparative statistics for DNA and protein sequences multiple sequence analysis. Proc. Natl. Acad. Sci. USA. 82:1985;6186-6190.
55. Karlin S., Ghandour G., Ost F., Tavare S., Korn L.J. New approaches for computer analysis of nucleic acid sequences. Proc. Natl. Acad. Sci. USA. 80:1983;5660-5664.
56. Karlin S., Ost F., Blaisdell B.E. Patterns in DNA and amino acid sequences and their statistical significance. Waterman M.S. Mathematical Methods for DNA Sequences. 1989;133-158 CRC Press.
57. Kim J., Klooster S., Shapiro D.J. Intrinsically bent DNA in a eukaryotic transcription factor recognition sequence potentiates transcription activation. J. Biol. Chem. 270:1995;1282-1288.
58. Klingenhoff A., Frech K., Quandt K., Werner T. Functional promoter modules can be detected by formal models independent of overall nucleotide sequence similarity. Bioinformatics. 15:1999;180-186.
59. Kolchanov N.A., Ponomarenko M.P., Kel A.E., et al. GeneExpress a computer system for description analysis and recognition of regulatory sequences in eukaryotic genome. Sixth International Symposium on Intelligent Systems for Molecular Biology. 1998;95-104 AAAI Press, Montréal, Canada.
60. Kondrakhin Y.U.V., Kolchanov N.A., Kel A.E., Romashchenko A.G., Milanesi L. Eukaryotic promoter recognition by binding sites for transcription factors. Comput. Appl. Biosci. 11:1995;477-488.
61. Krogh A., Mian I.S., Haussler D. A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res. 22:1994;4768-4778.
62. Lathrop R., Webster T., Smith R., Winston P., Smith T. Integrating AI with sequence analysis. Hunter L. Artificial Intelligence and Molecular Biology. 1993;211-258 AAAI Press/The MIT Pr.
63. Lavery R., Zakrzewska K., Pullmann B. Jumna (Junction minimization of nucleic acid structures. Comp. Phys. Commun. 91:1995;135-158.
64. Lawrence C.E., Altschul S.F., Boguski M.S., Liu J.S., Neuwald A.F., Wooton J.C. Detecting subtle sequence signals a Gibbs sampling strategy for multiple alignment. Science. 262:1993;208-214.
65. Lawrence C.E., Reilly A.A. An expectation maximization (EM) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences. Proteins Struct. Funct. Gen. 7:1990;41-51.
66. Levenshtein V.I. Binary codes capable of correcting deletions insertions and reversals. Cyber. Contr. Theory. 10:1966;707-710.
67. Lukashin A.V., Borodovsky M. GeneMark. hmm - new solutions for gene finding. Nucleic Acids Res. 26:1998;1107-1115.
68. Malladine C.R., ElHassan M.A. Propeller-twisting of base-pairs and the conformational mobility of dinucleotide steps in DNA. J. Mol. Biol. 259:1996;95-103.
69. Manber U., Myers E.W. Suffix arrays A new method for on-line string searches. SIAM J. Comp. 22:1993;935-948.
70. Marsan L., Sagot M. -F., Extracting structured motifs using a suffix tree - Algorithms and application to promoter consensus identification. RECOMB'2000. 1999;. in press.
71. McClure W.R. Mechanism and control of transcription initiation in prokaryotes. Annu. Rev. BioChem. 54:1985;171-204.
72. Mehldau G., Myers E.W. A system for pattern matching applications on biosequences. Comput. Appl. Biosci. 9:1993;299-314.
73. Mulder M.A., Zappe H., Steyn L.M. Mycobacterial promoters. Tuber. Lung Dis. 78:1997;211-223.
74. Mulligan M.E., Hawley D.K., Entriken R., McClure W.R. Escherichia coli promoter sequences predict in vitro RNA polymerase selectivity. Nucleic Acids Res. 12:1984;789-800.
75. Myers G., Guimaraes K., Oliva P. Reporting exact and approximate regular expression matches. Farach-Colton M. Combinatorial Pattern Matching, Lecture Notes in Computer Science (volume 1448). 1998;Springer-Verlag.
76. Neuwald A.F., Green P. Detecting patterns in protein sequences. J. Mol. Biol. 239:1994;698-712.
77. Ohler U., Harbeck S., Niemann H., Noth E., Reese M.G. Interpolated markov chains for eukaryotic promoter recognition. Bioinformatics. 15:1999;362-369.
78. O'Neill M.C. Consensus methods for finding and ranking DNA binding sites. Application to Escherichia coli. J. Mol. Biol. 207:1989;301-310.
79. O'Neill M.C. Escherichia coli promoters. I. Consensus as it relates to spacing class specificity repeat substructure and three-dimensional organization. J. Biol. Chem. 264:1989;5522-5530.
80. O'Neill M.C. Training back-propagation neural networks to define and detect DNA binding sites. Nucleic Acids Res. 19:1991;313-318.
81. O'Neill M.C., Chiafari F. Escherichia coli promoters. II. A spacing class-dependent promoter search protocol. J. Biol. Chem. 264:1989;5531-5534.
82. Ozoline O.N., Deev A.A., Arkhipova M.V. Non-canonical sequence elements in the promoter structure. cluster analysis of promoters recognized by Escherichia coli RNA polymerase. Nucleic Acids Res. 25:1998;4703-4709.
83. Pearson W.R. Rapid and sensitive sequence comparison with FASTP and FASTA. Meth. Enzymol. 183:1990;63-98.
84. Pearson W.R., Lipman D.J. Improved tools for biological sequence comparison. Proc. Natl. Acad. Sci. USA. 85:1988;2444-2448.
85. Pedersen A.G., Baldi P., Chauvin Y., Brunak S. DNA structure in human RNA polymerase II promoters. J. Mol. Biol. 281:1998;663-673.
86. Perez-Rueda E., Gralla J.D., Collado-Vides J. Genomic position analyses and the transcription machinery. J. Mol. Biol. 275:1998;165-170.
87. Pesole G., Prunella N., Liuni S., Attimonelli M., Saccone C. Wordup: an efficient algorithm for discovering statistically significant patterns in DNA sequences. Nucleic Acids Res. 20:1992;2871-2875.
88. Pickert L., Reuter I., Klawonn F., Wingender E. Transcription regulatory region analysis using signal detection and fuzzy clustering. Bioinformatics. 14:1998;244-251.
89. Press W.H., Teukolsky S.A., Vetterling W.T., Flannery B.P. Numerical Recipes in C - The Art of Scientific Computing. 1993;Cambridge Univ. Press.
90. Prestridge D.S. Predicting Pol II promoter sequence using transcription factor binding sites. J. Mol. Biol. 249:1995;923-932.
91. Prestridge D.S., Stormo G. SIGNAL SCAN a computer program that scans DNA sequences for eukaryotic transcriptional elements. Comput. Appl. Biosci. 7:1991;203-206.
92. Prestridge D.S., Stormo G. SIGNAL SCAN 3. 0 new database and program features. Comput. Appl. Biosci. 9:1993;113-115.
93. Quandt K., Grote K., Werner T. GenomeInspector: Basic software tools for analysis of spatial correlations between genomic structures within magabase sequences. Genomics. 33:1996;301-304.
94. Queen C., Wegman M.N., Korn L.J. Improvements to a program for DNA analysis a procedure to find homologies among many sequences. Nucleic Acids Res. 10:1982;449-456.
95. Record M.T., Reznikoff W.S., Craig M.L., McQuade K.L., Schlax P.J. Escherichia coli RNA polymerase s70 promoters and the kinetics of the steps of transcription initiation. in: Neidhardt editor Escherichia coli and Salmonella volume 1. 1996;792-820 ASM Press.
96. Régnier M., Szpankowski W. On the approximate pattern occurrences in a text. JOURNAL TITLE. VOLUME:1997;1-1.
97. Reinert G., Schbath S. Compound poisson and poisson process approximations for occurrences of multiple words in markov chains. J. Comp. Biol. 5:1998;223-253.
98. Roth F.P., Hughes J.D., Estep P.W., Church G.M. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation. Nat. Biotechnol. 16:1998;939-945.
99. Sagot M.F. Spelling approximate repeated or common motifs using a suffix tree. Lucchesi C.L, Moura A.V. LATIN'98 - Theoretical Informatics Lecture Notes in Computer Science (volume 1380). 1998;111-127 Springer-Verlag.
100. Sagot M.F., Escalier V., Viari A., Soldano H. Searching for repeated words in a text allowing for mismatches and gaps. Baeza-Yates R, Manber U. Second South American Workshop on String Processing. 1995;87-100 Viñas del Mar Chili, University of Chili.
101. Sagot M.F., Viari A. Double combinatorial approach to discovering patterns in biological sequences. Hirschberg D, Myers G. Combinatorial Pattern Matching, Lecture Notes in Computer Science (volume 1075). 1996;186-208 Springer-Verlag.
102. Sagot M.F., Viari A. Flexible identification of structural objects in nucleic acid sequences palindromes mirror repeats pseudoknots and triple helices. Hein J. Combinatorial Pattern Matching, Lecture Notes in Computer Science (volume 1264). 1997;224-246 Springer-Verlag.
103. Sagot M.F., Viari A., Soldano H. Multiple comparison a peptide matching approach. Theoret. Comput. Sci. 180:1997;115-137.
104. Salzberg S.L., Pertea M., Delcher A.L., Gardner M.J., Tettelin H. Interpolated markov models for eukaryotic gene finding. Genomics. 59:1999;24-31.
105. Saurin W., Marlière P. Matching relational patterns in nucleic acid sequences. Comput. Appl. Biosci. 3:1987;115-120.
106. Schbath S. An efficient statistic to detect over- and under-represented words in DNA sequences. J. Comp. Biol. 4:1997;189-192.
107. Schbath S., Prum B., DeTurcheim E. Exceptional motifs in different Markov chain models for a statistical analysis of DNA sequences. J. Comp. Biol. 2:1995;417-437.
108. Schneider T.D., Stormo G.D., Gold L., Ehrenfeucht A. Information content of binding sites on nucleotide sequences. J. Mol. Biol. 188:1986;415-431.
109. Sewell R.F., Durbin R. Method for calculation of matching a bounded regular expression in a random data string. J. Comput. Biol. 2:1995;25-31.
110. Staden R. Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res. 12:1984;505-519.
111. Staden R. Methods for calculating the probabilities of finding patterns in sequences. Comput. Appl. Biosci. 5:1989;89-96.
112. Staden R. Methods for discovering novel motifs in nucleic acid sequences. Comput. Appl. Biosci. 5:1989;293-298.
113. Stormo G.D. Computer methods for analyzing sequence recognition of nucleic acids. Annu. Rev. Biophys. Biophys. Chem. 17:1988;241-263.
114. Stormo G.D. Consensus patterns in DNA. Meth. Enzymol. 183:1990;211-221.
115. Stormo G.D., Hartzell I.I.I., Gw. Identifying protein-binding sites from unaligned DNA fragments. Proc. Natl. Acad. Sci. USA. 86:1989;1183-1187.
116. Tompa M. An exact method for finding short motifs in sequences with application to the ribosome binding site problem. Seventh International Symposium on Intelligent Systems for Molecular Biology. 1999;262-271 AAAI Press, Heidelberg, Germany.
117. Ulyanov A.V., Stormo G.D. Multi-alphabet consensus algorithm for identification of low specificity protein-DNA interactions. Nucleic Acids Res. 23:1995;1434-1440.
118. 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. 281:1998;827-842.
119. Vanet A., Marsan L., Labigne A., Sagot M.F. Inferring regulatory elements from a whole genome. An analysis of the s80 family of promoter signals. J. Mol. Biol. Vol. 1999.
120. Waterman M.S. General methods of sequence comparison. Bull. Math. Biol. 46:1984;473-500.
121. Waterman M.S. Multiple sequence alignments by consensus. Nucleic Acids Res. 14:1986;9095-9102.
122. Waterman M.S. Consensus patterns in sequences. Waterman M.S. Mathematical Methods for DNA Sequences. 1989;93-116 CRC Press.
123. Waterman M.S., Arratia R., Galas D.J. Pattern recognition in several sequences consensus and alignment. Bull. Math. Biol. 46:1984;515-527.
124. Werner T. Models for prediction and recognition of eukaryotic promoters. Mamm. Genome. 10:1999;168-175.
125. Wolfertstetter F., Frech K., Herrmann G., Werner T. Identification of functional elements in unaligned nucleic acid sequences by a novel tuple search algorithms. Comput. Appl. Biosci. 12:1996;71-80.
126. Yada T., Totoki Y., Ishikawa M., Asai K., Nakai K. Automatic extraction of motifs represented in the hidden Markov model from a number of DNA sequences. Bioinformatics. 14:1998;317-325.
127. Zhang M.Q. A discrimination study of human core-promoters. Pac. Symp. Biocomput. '98. 1998;240-251.
128. Zhang M.Q. Identification of human gene core promoters in silico. Genome Research. 8:1998;319-326.