In search of the small ones: Improved prediction of short exons in vertebrates, plants, fungi and protists

Bioinformatics

Volumn 23, Issue 4, 2007, Pages 414-420

  Saeys, Yvan ^a   Rouzé, Pierre ^b,c   Van de Peer, Yves ^a  

^a DEPARTMENT OF PLANT SYSTEMS BIOLOGY   (Belgium)

^b CEMAGREF   (France)

^c GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARABIDOPSIS; ARTICLE; CRYPTOCOCCUS NEOFORMANS; EUKARYOTE; EXON; FUNGUS; GENE SEQUENCE; GENETIC ANALYSIS; GENETIC CODE; GENOME; HUMAN; INTRON; NONHUMAN; PLANT; PLASMODIUM FALCIPARUM; PREDICTION; PRIORITY JOURNAL; PROBABILITY; SEQUENCE ANALYSIS; STATISTICAL MODEL; VERTEBRATE;

EUKARYOTA; FUNGI; PROTISTA; VERTEBRATA;

EID: 33847329566     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btl639     Document Type: Article

References (27)

1. Bertone,P. et al. (2006) Global identification of human transcribed sequences with genome tiling arrays. Science, 306, 2242-2246.
2. Borodovsky,M. and McIninch,J. (1993) Genmark: Parallel gene recognition for both DNA strands. Comput. Chem., 17, 123-133.
3. Boser,B.E. et al. (1992) A training algorithm for optimal margin classifiers. In Proceedings of Fifth ACM Workshop on COLT, pp. 144-152.
4. Brent,M.R. and Guigó,R. (2004) Recent advances in gene structure prediction. Curr. Opin. Struct. Biol., 14, 264-272.
5. Fickett,J. and Tung,C. (1992) Assessment of protein coding measures. Nucleic Acids Res., 20, 6441-6450.
6. Gao,F. and Zhang,C.T. (2004) Comparison of various algorithms for recognizing short coding sequences of human genes. Bioinformatics, 20, 673-681.
7. International Human Genome Sequencing Consortium (2004), Finishing the euchromatic sequence of the human genome. Nature, 431, 931-945.
8. Joachims,T. (1998) Making large-scale support vector machine learning practical. In Schoelkopf,B. et al. (eds), Advances in Kernel Methods: Support Vector Machines, pp. 169-184.
9. Kohavi,R. and John,G. (1997) Wrappers for feature subset selection. Artif. Intell., 97, 273-324.
10. Koller,D. and Sahami,M. (1996) Toward optimal feature selection. In Proceedings of the 13th International Conference on Machine Learning, pp. 284-292.
11. Kotlar,D. and Lavner,Y. (2003) Gene prediction by spectral rotation measure: A new method for identifying protein-coding regions. Genome Res., 13, 1930-1937.
12. Majoros,W.H. et al. (2003) GlimmerM, Exonomy and Unveil: Three ab initio eukaryotic genefinders. Nucleic Acids Res., 31, 3601-3604.
13. Majoros,W.H. et al. (2004) TigrScan and GlimmerHMM: Two open source ab initio eukaryotic gene-finders. Bioinformatics, 20, 2878-2879.
14. Mathé,C. et al. (2002) Current methods of gene prediction, their strengths and weaknesses. Nucleic Acids Res., 30, 4103-4117.
15. Ng,A.N. and Jordan,M. (2002) On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes. In Advances in Neural Information Processing Systems 14. MIT Press, Cambridge, MA.
16. Provost,F.J. and Fawcett,T. (1997) Analysis and visualization of classifier performance: Comparison under imprecise class and cost distributions. In Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, pp. 43-48.
17. Raudys,S. and Jain,A. (1991) Small sample size effects in statistical pattern recognition: Recommendations for practitioners. IEEE Trans. PAMI, 13, 252-264.
18. Saeys,Y. (2004) Feature selection for splice site prediction: A new method using EDA-based feature ranking. BMC Bioinformatics, 21, 64.
19. Salzberg,S.L. et al. (1998) Microbial gene identification using interpolated Markov models. Nucleic Acids Res., 26, 544-548.
20. Salzberg,S. et al. (1999) Interpolated Markov models for eukaryotic gene finding. Genomics, 59, 24-31.
21. Schiex,T. et al. (2001) EuGène: An Eukaryotic Gene Finder that combines several sources of evidence. In Gascuel, O. and Sagot, M.-F. (eds), Proceedings of the Lect. Notes Comput. Sc. 2006, pp. 111-125.
22. Silverman,B. and Linsker,R. (1986) A measure of DNA periodicity. J. Theor. Biol., 118, 295-300.
23. Stanke,M. et al. (2006) Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics, 7, 62.
24. Stolc,V. et al. (2005) Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays. Proc. Natl Acad. Sci. USA, 102, 4453-4458.
25. Tiwari,S. et al. (1997) Prediction of probable genes by Fourier analysis of genomic sequences. Comput. Appl. Biosci., 13, 263-270.
26. Voss,R. (1992) Evolution of long-range fractal correlations and 1/f noise in DNA base sequences. Phys. Rev. Lett., 68, 3805-3808.
27. Wang,Y. et al. (2002) Recognizing shorter coding regions of human genes based on the statistics of stop codons. Biopolymers, 63, 207-216.