Genome-specific higher-order background models to improve motif detection

Trends in Microbiology

Volumn 11, Issue 2, 2003, Pages 61-66

  Marchal, Kathleen ^a   Thijs, Gert ^a   De Keersmaecker, Sigrid ^a   Monsieurs, Pieter ^a   De Moor, Bart ^a   Vanderleyden, Jos ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

NUCLEOTIDE;

BACTERIAL GENOME; ESCHERICHIA COLI K 12; GENE SEQUENCE; GENOME ANALYSIS; LISTERIA MONOCYTOGENES; MOLECULAR MODEL; NONHUMAN; PRIORITY JOURNAL; PROKARYOTE; PROTEIN MOTIF; PSEUDOMONAS AERUGINOSA; REVIEW; SPECIES DIFFERENCE; STREPTOMYCES COELICOLOR;

BACTERIA (MICROORGANISMS); ESCHERICHIA COLI; ESCHERICHIA COLI K12; LISTERIA; LISTERIA MONOCYTOGENES; PROKARYOTA; PSEUDOMONAS; PSEUDOMONAS AERUGINOSA; STREPTOMYCES; STREPTOMYCES COELICOLOR;

EID: 0037323120     PISSN: 0966842X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0966-842X(02)00030-6     Document Type: Review

References (17)

1. Brazma A., et al. Minimum information about a microarray experiment (MIAME) - toward standards for microarray data. Nat. Genet. 29:2001;365-371.
2. Moreau Y., et al. Functional bioinformatics of microarray data: from expression to regulation. IEEE Proceedings. 11:2002;1722-1743.
3. Manson M.A., Church G.M. Predicting regulons and their cis-regulatory motifs by comparative genomics. Nucleic Acids Res. 28:2000;4523-4530.
4. McCue L.A., et al. Factors influencing the identification of transcription factor binding sites by cross-species comparison. Genome Res. 12:2002;1523-1532.
5. Lawrence C.E., et al. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science. 262:1993;208-214.
6. Liu X., et al. BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes. Pac. Symp. Biocomput. 6:2001;127-138. http://psb.stanford.edu/psb-online/.
7. Bailey T.L., Elkan C. The value of prior knowledge in discovering motifs with MEME. Proc. Int. Conf. Intell. Syst. Mol. Biol. 3:1995;21-29.
8. Thijs G., et al. A Gibbs sampling method to detect overrepresented motifs in the upstream regions of coexpressed genes. J. Comput. Biol. 9:2002;447-464.
9. Workman C.T., Stormo G.D. ANN-Spec: a method for discovering transcription factor binding sites with improved specificity. Pac. Symp. Biocomput. 5:2000;467-478. http://psb.stanford.edu/psb-online/.
10. McCue L., et al. Phylogenetic footprinting of transcription factor binding sites in proteobacterial genomes. Nucleic Acids Res. 29:2001;774-782.
11. McGuire A.M., et al. Conservation of DNA regulatory motifs and discovery of new motifs in microbial genomes. Genome Res. 10:2000;744-757.
12. Thijs G., et al. A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling. Bioinformatics. 17:2001;1113-1122.
13. Thijs G., et al. INCLUSive: INtegrated Clustering, Upstream sequence retrieval and motif Sampling. Bioinformatics. 18:2002;331-332.
14. Barrios H., et al. Compilation and analysis of σ(54)-dependent promoter sequences. Nucleic Acids Res. 27:1999;4305-4313.
15. Dombrecht B., et al. Prediction and overview of the RpoN-regulon in closely related species of the Rhizobiales. Genome Biol. 2002;research0076.1-0076.11.
16. Reitzer L., Schneider B.L. Metabolic context and possible physiological themes of σ(54)-dependent genes in Escherichia coli. Microbiol. Mol. Biol. Rev. 65:2001;422-444.
17. Benson D.A., et al. GenBank. Nucleic Acids Res. 30:2002;17-20.