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Volumn 33, Issue 1, 2003, Pages 17-29

Identifying splicing sites in eukaryotic RNA: Support vector machine approach

Author keywords

Neural network; RNA secondary structure; Sensitivity; Specificity; Splice site; Support vector machines (SVM)

Indexed keywords

PATTERN RECOGNITION; RNA; STATISTICAL METHODS;

EID: 0037212915     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0010-4825(02)00057-4     Document Type: Article
Times cited : (59)

References (25)
  • 1
    • 0030971398 scopus 로고    scopus 로고
    • A study of learning splice sites of DNA sequence by neural networks
    • Ogura H., Agala H.et al. A study of learning splice sites of DNA sequence by neural networks. Comput. Biol. Med. 27:1997;67-75.
    • (1997) Comput. Biol. Med. , vol.27 , pp. 67-75
    • Ogura, H.1    Agala, H.2
  • 2
    • 0035957531 scopus 로고    scopus 로고
    • A novel method of protein secondary structure prediction with high segment overlap measure: Support vector machine approach
    • Hua S., Sun Z. A novel method of protein secondary structure prediction with high segment overlap measure. support vector machine approach J. Mol. Biol. 308(2):2001;397-407.
    • (2001) J. Mol. Biol. , vol.308 , Issue.2 , pp. 397-407
    • Hua, S.1    Sun, Z.2
  • 7
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes C., Vapnik V. Support vector networks. Mach. Learning. 20:1995;273-293.
    • (1995) Mach. Learning , vol.20 , pp. 273-293
    • Cortes, C.1    Vapnik, V.2
  • 8
    • 0032594950 scopus 로고    scopus 로고
    • Support vector machines for spam categorization
    • Drucker H., Wu D., Vapnik V. Support vector machines for spam categorization. IEEE Trans. Neural Networks. 10:1999;1054-1084.
    • (1999) IEEE Trans. Neural Networks , vol.10 , pp. 1054-1084
    • Drucker, H.1    Wu, D.2    Vapnik, V.3
  • 9
    • 0033347943 scopus 로고    scopus 로고
    • View-based 3D object recognition with Support Vector Machines
    • Y.H. Hu, J. Larsen, E. Wilson, & S. Douglas. New Jersey: IEEE Press
    • Roobaert D., Hulle M.M. View-based 3D object recognition with Support Vector Machines. Hu Y.H., Larsen J., Wilson E., Douglas S. Proceedings of the IEEE Neural Networks for Signal Proceeding Workshop. 1999;77-84 IEEE Press, New Jersey.
    • (1999) Proceedings of the IEEE Neural Networks for Signal Proceeding Workshop , pp. 77-84
    • Roobaert, D.1    Hulle, M.M.2
  • 11
    • 0035875551 scopus 로고    scopus 로고
    • Human GC-AG alternative intron isoforms with weak donor sites show enhanced consensus at acceptor exon positions
    • Thanaraj T.A., Clark F. Human GC-AG alternative intron isoforms with weak donor sites show enhanced consensus at acceptor exon positions. Nucl. Acids Res. 29:2001;2581-2593.
    • (2001) Nucl. Acids Res. , vol.29 , pp. 2581-2593
    • Thanaraj, T.A.1    Clark, F.2
  • 12
    • 0033168964 scopus 로고    scopus 로고
    • A clean data set of EST-confirmed splice sites fome Homo sapiens and standards for clean-up procedures
    • Thanaraj T.A. A clean data set of EST-confirmed splice sites fome Homo sapiens and standards for clean-up procedures. Nucl. Acids Res. 27:1999;2627-2637.
    • (1999) Nucl. Acids Res. , vol.27 , pp. 2627-2637
    • Thanaraj, T.A.1
  • 13
    • 0035165586 scopus 로고    scopus 로고
    • SpliceDB: Database of canonical and non-canonical mammalian splice sites
    • Burset M., Seledtsov I.A., Solovyev V.V. SpliceDB. database of canonical and non-canonical mammalian splice sites Nucl. Acids Res. 29:2001;255-259.
    • (2001) Nucl. Acids Res. , vol.29 , pp. 255-259
    • Burset, M.1    Seledtsov, I.A.2    Solovyev, V.V.3
  • 14
    • 0024477261 scopus 로고
    • On finding all suboptimal foldings of an RNA molecule
    • Zuker M. On finding all suboptimal foldings of an RNA molecule. Science. 244:1989;48-52.
    • (1989) Science , vol.244 , pp. 48-52
    • Zuker, M.1
  • 15
    • 0001947120 scopus 로고
    • The use of dynamic programming algorithms in RNA secondary structure prediction
    • M.S. Waterman. Boca Raton, FL: CRC Press
    • Zuker M. The use of dynamic programming algorithms in RNA secondary structure prediction. Waterman M.S. Mathematical Methods for DNA Sequences. 1989;159-184 CRC Press, Boca Raton, FL.
    • (1989) Mathematical Methods for DNA Sequences , pp. 159-184
    • Zuker, M.1
  • 16
    • 0019876473 scopus 로고
    • Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information
    • Zuker M., Stiegler P. Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucl. Acids Res. 9:1981;133-148.
    • (1981) Nucl. Acids Res. , vol.9 , pp. 133-148
    • Zuker, M.1    Stiegler, P.2
  • 17
    • 0025264854 scopus 로고
    • The equilibrium partition function and base pair binding probabilities for RNA secondary structure
    • McCaskill J.S. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers. 29:1990;1105-1119.
    • (1990) Biopolymers , vol.29 , pp. 1105-1119
    • McCaskill, J.S.1
  • 18
    • 34249772381 scopus 로고
    • Fast folding and comparison of RNA secondary structure
    • Hofacker I.L., Fontana W., Stadler P.F.et al. Fast folding and comparison of RNA secondary structure. Monatsh. Chem. 125:1994;167-188.
    • (1994) Monatsh. Chem. , vol.125 , pp. 167-188
    • Hofacker, I.L.1    Fontana, W.2    Stadler, P.F.3
  • 19
    • 0033563515 scopus 로고    scopus 로고
    • A Bayesian statistical algorithm for RNA secondary structure prediction
    • Ding Y., Lawrence C.E. A Bayesian statistical algorithm for RNA secondary structure prediction. Comput. Chem. 23:1999;387-400.
    • (1999) Comput. Chem. , vol.23 , pp. 387-400
    • Ding, Y.1    Lawrence, C.E.2
  • 20
    • 0035283171 scopus 로고    scopus 로고
    • Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond
    • Ding Y., Lawrence C.E. Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond. Nucl. Acids Res. 29:2001;1034-1046.
    • (2001) Nucl. Acids Res. , vol.29 , pp. 1034-1046
    • Ding, Y.1    Lawrence, C.E.2
  • 22
    • 0034662286 scopus 로고    scopus 로고
    • Recognition of protein coding genes in the yeast genome at better than 95% accuracy based on Z curve
    • Zhang C.-T., Wang J. Recognition of protein coding genes in the yeast genome at better than 95% accuracy based on Z curve. Nucl. Acids Res. 28:2000;2804-2814.
    • (2000) Nucl. Acids Res. , vol.28 , pp. 2804-2814
    • Zhang, C.-T.1    Wang, J.2
  • 23
    • 0001256503 scopus 로고
    • A stochastic approach to genetic information processing
    • Konagaya A. A stochastic approach to genetic information processing. J. Jpn. Soc. Artif. Intell. 8:1993;427-438.
    • (1993) J. Jpn. Soc. Artif. Intell. , vol.8 , pp. 427-438
    • Konagaya, A.1
  • 24
    • 0028605559 scopus 로고
    • Constructing gene models from accurately predicted exons: An application of dynamic programming
    • Xu Y., Mural R.J., Uberbacher E.C. Constructing gene models from accurately predicted exons. an application of dynamic programming CABIOS. 10:1994;613-623.
    • (1994) CABIOS , vol.10 , pp. 613-623
    • Xu, Y.1    Mural, R.J.2    Uberbacher, E.C.3
  • 25
    • 0029075793 scopus 로고
    • Correcting sequencing errors in DNA coding regions using a dynamic programming approach
    • Xu Y., Mural R.J., Uberbacher E.C. Correcting sequencing errors in DNA coding regions using a dynamic programming approach. CABIOS. 11:1995;117-124
    • (1995) CABIOS , vol.11 , pp. 117-124
    • Xu, Y.1    Mural, R.J.2    Uberbacher, E.C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.