Improved prediction of bacterial transcription start sites

Bioinformatics

Volumn 22, Issue 2, 2006, Pages 142-148

  Gordon, J J ^a   Towsey, M W ^a   Hogan, J M ^a   Mathews, S A ^a   Timms, P ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BACTERIAL GENETICS; BINDING SITE; COMPUTER MODEL; DATA BASE; ESCHERICHIA COLI; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; INTERMETHOD COMPARISON; METHODOLOGY; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROMOTER REGION; SCORING SYSTEM; STRUCTURAL GENOMICS; TRANSCRIPTION INITIATION SITE; TRANSCRIPTION REGULATION;

BACTERIA (MICROORGANISMS); ESCHERICHIA COLI;

EID: 32144448660     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/bti771     Document Type: Article

References (18)

1. Burden,S. et al. (2005) Improving promoter prediction for the NNPP2.2 algorithm: A case study using Escherichia coli DNA sequences. Bioinformatics, 21, 601-607.
2. Duda,R.O., Hart,P.E. and Stork,D.G. (2001) Pattern Classification. John Wiley & Sons, New York.
3. Gordon,J.J. and Towsey,M. (2005) SVM based prediction of bacterial transcription start sites. In Proceedings 6th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'05), Brisbane, Australia, July 2005 Lecture Notes in Computer Science, 3578, 448, Springer, Berlin.
4. Gordon,L. (2003) Sequence alignment kernel for recognition of promoter regions. Bioinformatics, 19, 1964-1971.
5. Gourse,R.L. et al. (2000) Ups and downs in bacterial transcription initiation: The role of the alpha subunit of RNA polymerase in promoter recognition. Mol. Biol., 37, 687-695.
6. Hatzigeorgiou,A.G. (2002) Translation initiation start prediction in human cDNAs with high accuracy. Bioinformatics, 18, 343-350.
7. Huerta,A.M. and Collado-Vides,J. (2003) Sigma-70 promoters in E. coli: specific transcription in dense regions of overlapping promoter-like signals. J. Mol. Biol., 333, 261-278.
8. Joachims,T. (1999) Making large scale SVM learning practical. In Scholkopf,B., Burges,C. and Smola,A. (eds). Advances Kernel Methods - Support Vector Learning. MIT Press, Cambridge, MA.
9. Leslie,C.S. et al. (2004) Mismatch string kernels for discriminative protein classification. Bioinformatics, 20, 467-476.
10. Lewin,B. (1985) Genes. John Wiley & Sons, New York.
11. Liu,H. and Wong,L. (2003) Data mining tools for biological sequences. J. Bioinform. Comp. Biol., 1, 139-167.
12. Salgado,H. et al. (2001) RegulonDB (version 3.2): Transcriptional regulation and operon organization in E. coli K-12. Nucleic Acids Res., 29, 72-74.
13. Sambrook,J., Fritsch,E.F. and Maniatis,T. (1989) Molecular Cloning: A Laboratory Manual. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, ISBN:0-87969-309-6.
14. Schneider,T.D. (1997) Information content of individual genetic sequences. J. Theor. Biol., 189, 427-441.
15. Schneider,T.D. et al. (1986) Information content of binding sites on nucleotide sequences. J. Mol. Biol., 188, 415-431.
16. Serrafini,T., Zanghirati,G. and Zanni,L. (2004) Parallel GPDT: A parallel gradient projection-based decomposition technique for support vector machines.
17. Stormo,G. (2000) DNA binding sites: Representation and discovery. Bioinformatics, 16, 16-23.
18. Vapnik,V. (1995) The Nature of Statistical Learning Theory. Springer-Verlag, NY.