Condition specific transcription factor binding site characterization in Saccharomyces cerevisiae

Bioinformatics

Volumn 18, Issue 10, 2002, Pages 1289-1296

  Harrison, Rhonda ^a,b   DeLisi, Charles ^a  

^a BOSTON UNIVERSITY   (United States)

^b WHITEHEAD INSTITUTE FOR BIOMEDICAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR; FUNGAL PROTEIN; GAL4 PROTEIN, S CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEIN; STE12 PROTEIN, FUNGUS; STE12 PROTEIN, S CEREVISIAE;

ARTICLE; BINDING SITE; BIOINFORMATICS; CONTROLLED STUDY; NONHUMAN; OPEN READING FRAME; PRIORITY JOURNAL; PROMOTER REGION; PROTEIN BINDING; PROTEIN MOTIF; QUALITY CONTROL; SACCHAROMYCES CEREVISIAE; SEQUENCE ALIGNMENT; TRANSCRIPTION REGULATION; CONSENSUS SEQUENCE; DATA BASE; EVALUATION; GENE EXPRESSION REGULATION; GENETIC DATABASE; GENETICS; GENOME; INFORMATION RETRIEVAL; INTERNET; METABOLISM; METHODOLOGY; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROTEIN DATABASE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS;

SACCHAROMYCES; SACCHAROMYCES CEREVISIAE;

AMINO ACID MOTIFS; BASE SEQUENCE; BINDING SITES; CONSENSUS SEQUENCE; DATABASE MANAGEMENT SYSTEMS; DATABASES, GENETIC; DATABASES, PROTEIN; FUNGAL PROTEINS; GENE EXPRESSION REGULATION, FUNGAL; GENOME, FUNGAL; INFORMATION STORAGE AND RETRIEVAL; INTERNET; MOLECULAR SEQUENCE DATA; OPEN READING FRAMES; PROTEIN BINDING; QUALITY CONTROL; REPRODUCIBILITY OF RESULTS; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; TRANSCRIPTION FACTORS;

EID: 0036773460     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/18.10.1289     Document Type: Article

References (19)

1. Bailey,T.L. and Elkan,C. (1995) Unsupervised learning of multiple motifs in biopolymers using expecation maximization. Mach. Learn. J., 21, 51-83.
2. DeRisi,J.L., Iyer,V.R. and Brown,P.O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science, 278, 680-686.
3. Hughes,J.D., Estep,P.W., Tavazoie,S. and Church,G.M. (2000) Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae. J. Mol. Biol., 296, 1205-1214.
4. Frech,K., Danescu-Mayer,J. and Werner,T. (1997) A novel method to develop highly specific models for regulatory units detects a new LTR in GenBank which contains a functional promoter. J. Mol. Biol., 270, 674-687.
5. Klingenhoff,A., Frech,K., Quandt,K. and Werner,T. (1999) Functional promoter modules can be detected by formal models independent of overall nucleotide sequence similarity. Bioinformatics, 15, 180-186.
6. Lawrence,C.E., Altschul,S.F., Boguski,M.S., Liu,J.S., Neuwald,A.F. and Wootton,J.C. (1993) Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science, 262, 208-214.
7. Liu,X., Brutlag,D.L. and Liu,J.S. (2001) BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes. In Proceedings of Pacific Symposium on Bicomputing 2001. pp. 127-138.
8. Marmolstein,R., Carey,M., Ptashne,M. and Harrison,S. (1992) DNA Recognition by Ga14: structure of a protein-DNA complex. Nature, 356, 408-414.
9. Pesole,G., Liuni,S. and D'Souza,M. (2000) PatSearch: a pattern matcher software that finds functional elements in nucleotide and protein sequences and assesses their statistical significance. Bioinformatics, 16, 439-450.
10. Prestridge,D.S. (1991) SIGNAL SCAN: A computer program that scans DNA sequences for eukaryotic transcriptional elements. CABIOS, 7, 203-206.
11. Prestidge,D.S. (1995) Predicting pol II promoter sequences using transcirption factor binding sites. J. Mol. Biol., 249, 923-932.
12. Ren,B., Robert,F., Wyrick,J., Aparicio,O., Jennings,E.G., Simon,I., Zeitlinger,J., Shreiber,J., Hannett,N., Kanin,E. et al. (2000) Genome-wide Location and Function of DNA-binding Proteins. Science, 290, 2306-2309.
13. Rippe,R.A., Brenner,D.A. and Tugores,A. (2001) Techniques to measure nucleic acid-protein binding and specificity. Nuclear extract preparations, DNase I, footprinting, and mobility shift assays. Methods Mol. Biol., 160, 459-479.
14. Roth,F.R., Hughes,J.D., Estep,P.E. and Church,G.M. (1998) Finding DNA regulatory motifs within unaligned non-coding sequences clustered by whole-genome mRNA quantitation. Nat. Biotechnol., 16, 939-945.
15. Schug,J. and Overton,G.C. (1997) TESS: Transcription Element Search Software on the WWW, Technical Report CBIL-TR-1997-1001-v0.0, of the Computational Biology and Informatics Laboratory, School of Medicine, University of Pennsylvania.
16. Thompson,J.D., Higgins,D.G. and Gibson,T.J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res., 22, 4673-4680.
17. Waibel,A.H., Hanazawa,T., Hinton,G.E., Shikano,K. and Lang,K.J. (1989) Pheneme recognition using time-delay neural networks. IEEE Trans. Acoust. Speech and Signal Process., 37, 328-339.
18. Wingender,E., Chen,X., Fricke,E., Geffers,R., Hehl,R., Liebich,I., Krull,M., Matys,V., Michael,H., Ohnhauser,R. et al. (2001) The TRANSFAC system on gene expression regulation. Nucleic Acids Res., 29, 281-283.
19. Zhu,J. and Zhang,M.Q. (1999) SCPD: a promoter database of the yeast Saccharomyces cerevisiae. Bioinformatics, 15, 607-611.