A machine learning strategy to identify candidate binding sites in human protein-coding sequence

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Down, Thomas ^a   Leong, Bernard ^a   Hubbard, Tim J P ^a  

^a WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CANDIDATE SEQUENCES; COMPUTATIONAL MODEL; EXON SEQUENCES; LEARNING STRATEGY; PRIMARY FUNCTIONS; PROTEIN-CODING; REGULATORY ELEMENTS; SPLICING FACTORS;

LEARNING SYSTEMS; ORTHOGONAL FUNCTIONS; RNA;

PROTEINS;

DINUCLEOTIDE; PROTEIN; PROTEIN BINDING; TRANSCRIPTION FACTOR;

ARTICLE; BINDING SITE; EXON; GENE SEQUENCE; GENETIC CODE; HUMAN; MACHINE; MATHEMATICAL MODEL; PROTEIN MOTIF; RNA SPLICING; SENSITIVITY AND SPECIFICITY; SIGNAL DETECTION; ALGORITHM; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHEMICAL MODEL; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; DNA SEQUENCE; GENETICS; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROCEDURES; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; BASE SEQUENCE; BINDING SITES; COMPUTER SIMULATION; HUMANS; MODELS, CHEMICAL; MODELS, MOLECULAR; MOLECULAR SEQUENCE DATA; PATTERN RECOGNITION, AUTOMATED; PROTEIN BINDING; PROTEINS; SEQUENCE ANALYSIS, DNA; SEQUENCE ANALYSIS, PROTEIN; TRANSCRIPTION FACTORS;

EID: 33749615646     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-419     Document Type: Article

References (30)

1. Lim LP, Burge CB: A computational analysis of sequence features involved in recognition of short introns. Proc Natl Acad Sci USA 2001, 98(20):11193-11198.
2. Graveley BR: Sorting out the complexities of SR protein functions. RNA 2000, 6:1197.
3. Bourgeois CF, Popielarz M, Hildwein G, Stevenin J: Identification of a bidirectional splicing enhancer: differential involvement of SR proteins in 5′ or 3′ splice site activation. Mol Cell Biol 1999, 19:7347-7356.
4. Liu HX, Zhang M, Krainer AR. Identification of functional exonic splicing enhancers motifs recognized by individual SR proteins Genes Dev 1998, 12:1998-2012.
5. Lynch KW, Maniatis T: Assembly of specific SR protein complexes on distinct regulatory elements of the Drosophila doublesex splicing enhancer. Genes Dev 1996, 10:2089-2101.
6. Schaal TD, Maniatis T: Selection and characterization of premRNA splicing enhancers: identification of novel SR protein-specific enhancers sequences. Mol Cell Biol 1999, 19:1705-1719.
7. Tacke R, Manley JL: The human splicing factors ASF/SF2 and SC35 possess distinct functionally significant RNA binding specificities. EMBO J 1995, 14:3540-3551.
8. Tacke R, Tohyama M, Ogawa S, Manley JL: Human Tra2 proteins are sequence specific activators of pre-mRNA splicing. Cell 1999, 93:139-148.
9. Tian H, Kole R: Strong RNA splicing enhancers identified by a modified method of cycled selection interact with SR protein. J Biol Chem 2001, 276:33833-33839.
10. Zheng ZM, Huynen M, Baker CC: A pyrimidine-rich exonic splicing suppressor binds multiple RNA splicing factors and inhibits spliceosome assembly. Proc Natl Acad Sci USA 1998, 95:14088-93.
11. Cavaloc Y, Bourgeois CF, Kister L. Stevenin J: The splicing factors 9G8 and SRp20 transactivate splicing through different and specific enhancers. RNA 1999, 5:468-483.
12. Liu HX, Cartegni L, Zhang M, Krainer A: Exonic Splicing enhancer motif recognized by SC35 under splicing conditions. Mol Cell Bio 2000, 20(3):1063-1071.
13. Lam BJ, Hertel KJ: A general role for splicing enhancers in exon definition. RNA 2002, 8:1233-1241.
14. Ashurst JL, Chen C, Gilbert J, Jekosch K, Keenan S, Meidl P, Searle S, Stalker J, Storey R, Trevanion S, Wilming L, Hubbard T: The Vertebrate Genome Annotation Database. Nucleic Acids Res 2005, 33:D459-465.
15. Down TA, Hubbard TJP: What can we learn from noncoding regions of similarity between genomes. BMC Bioinformatics 2002, 5:144.
16. Bucher P: Weight matrix descriptions of four eukaryotic RNA polymerase II promoter elements derived from 502 unrelated promoter sequences. Journal of Molecular Biology 1990, 212:563-578.
17. Zhang XHF, Leslie CS, Chasin LA: Dichotomous Splicing Signals in Exon Flanks. Genome Res 2005, 15(6):768-79.
18. Katz L, Burge CB: Widespread Selection for Local RNA Secondary Structure in Coding Regions of Bacterial Genes. Genome Res 2003, 13:2042-2051.
19. Fairbrother WG, Yen RF, Sharp PA, Burge CB: Predictive Identification of Exonic Splicing Enhancers in human genes. Science 2002, 297:1007-1013.
20. Zhang HF, Heller KA, IH, Leslie CS, Chasin LA: Sequence Information for the Splicing of Human Pre-mRNA Identified by Support Vector Machine Classification. Genome Res 2003, 13(12):2637-2650.
21. Blanchette M: A comparative analysis method for detecting binding sites in coding regions. Proceedings of the seventh annual international conference on Research in computational molecular biology. 2003:57-66.
22. Dror G, Sorek R, Shamir R: Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics 2005, 21(7):897.
23. Down TA: Computational Localization of Promoters and Transcription Start Sites in Mammalian Genomes. In PhD thesis University of Cambridge; 2003.
24. Clark F, Thanaraj TA: Categorization and characterization of transcript-confirmed constitutively and alternatively spliced introns and exons from human. Human Molecular Genetics 2002, 11:451-464.
25. Birney E, et al: An Overview of Ensembl. Genome Res 2004, 14:925-928.
26. The Biojava Project [http://www.biojava.org]
27. Altschul SF, Madden T, Schaffer A, Zhang J, Zhang Z, Miller W, Lipman D: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-3402.
28. Metropolis N, Rosenbluth A, Rosenbluth M, Teller A, Teller E: Equation of state calculations by fast computing machines. J Chemical Physics 1953, 21:1087-1092.
29. Tipping ME: Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research 2000, 1:211-244.
30. Graepel T, Herbrich R, Shawe-Taylor J: Generalisation Error Bounds for Sparse Linear Classifiers. Proceedings of the Thirteenth Annual Conference on Computational Learning Theory 2000:298-303.