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Volumn 1, Issue , 2005, Pages 33-40

Evolving Hidden Markov Models for protein secondary structure prediction

Author keywords

[No Author keywords available]

Indexed keywords

BAUM-WELCH ALGORITHM; DATA SETS; HIDDEN MARKOV MODELS (HMM); PROTEIN SECONDARY STRUCTURE;

EID: 27144535913     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (11)

References (25)
  • 1
    • 0034604368 scopus 로고    scopus 로고
    • HMMSTR: A Hidden Markov Model for local sequence-structure correlations in proteins
    • C. Bystroff, V. Thorsson, and D. Baker, "HMMSTR: a Hidden Markov Model for Local Sequence-Structure Correlations in Proteins," Journal of Molecular Biology, vol. 301, pp. 173-190, 2000.
    • (2000) Journal of Molecular Biology , vol.301 , pp. 173-190
    • Bystroff, C.1    Thorsson, V.2    Baker, D.3
  • 2
    • 0033578684 scopus 로고    scopus 로고
    • Protein secondary structure prediction based on position-specific scoring matricws
    • D. T. Jones, "Protein Secondary Structure Prediction Based on Position-specific Scoring Matricws," Journal of Molecular Biology, vol. 292, pp. 195-202, 1999.
    • (1999) Journal of Molecular Biology , vol.292 , pp. 195-202
    • Jones, D.T.1
  • 3
    • 0036568279 scopus 로고    scopus 로고
    • Improving the prediction of protein secondary structure in three and egight classes using recurrent neural networks and profiles
    • G. Pollastri, D. Przybylski, B. Rost, and P. Baldi, "Improving the Prediction of Protein Secondary Structure in Three and Egight Classes Using Recurrent Neural Networks and Profiles," PROTEINS: Structure, Fuction, and Genetics, vol. 47, pp. 228-235, 2002.
    • (2002) PROTEINS: Structure, Fuction, and Genetics , vol.47 , pp. 228-235
    • Pollastri, G.1    Przybylski, D.2    Rost, B.3    Baldi, P.4
  • 4
    • 13444266488 scopus 로고    scopus 로고
    • A simple and fast secondary structure prodiction method using hidden neural networks
    • K. Lin, V. A. Simossis, W. R. Taylor, and J. Heringa, "A simple and fast secondary structure prodiction method using hidden neural networks," Bioinformatics, vol. 21, no. 2, pp. 152-159, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.2 , pp. 152-159
    • Lin, K.1    Simossis, V.A.2    Taylor, W.R.3    Heringa, J.4
  • 5
    • 0141738785 scopus 로고    scopus 로고
    • Secondary structure prediction with support vector machines
    • J. J. Ward, L. J. McGuffin, B. F. Buxton, and D. T. Jones, "Secondary structure prediction with support vector machines," Bioinformatics, vol. 19, no. 13, pp. 1650-1655, 2003.
    • (2003) Bioinformatics , vol.19 , Issue.13 , pp. 1650-1655
    • Ward, J.J.1    McGuffin, L.J.2    Buxton, B.F.3    Jones, D.T.4
  • 6
    • 1542346418 scopus 로고    scopus 로고
    • A novel method for protein secondary structure prediction using dual-layer SVM and profiles
    • J. Quo, H. Chen, Z. Sun, and Y. Lin, "A Novel Method for Protein Secondary Structure Prediction Using Dual-Layer SVM and Profiles," PROTEINS: Structure, Function, and Bioinformatics, vol. 54, pp. 738-743, 2004.
    • (2004) PROTEINS: Structure, Function, and Bioinformatics , vol.54 , pp. 738-743
    • Quo, J.1    Chen, H.2    Sun, Z.3    Lin, Y.4
  • 8
    • 12344325673 scopus 로고    scopus 로고
    • Training HMM structure with genetic algorithms for biological sequence analysis
    • K.-J. Won, A. Prügel-Bennett, and A. Krogh, "Training HMM Structure with Genetic Algorithms for Biological Sequence Analysis," Bioinformatics, vol. 20, no. 18, pp. 3613-3627, 2004.
    • (2004) Bioinformatics , vol.20 , Issue.18 , pp. 3613-3627
    • Won, K.-J.1    Prügel-Bennett, A.2    Krogh, A.3
  • 9
    • 27144531458 scopus 로고    scopus 로고
    • Evolving the structure of Hidden Markov Models
    • accepted
    • _, "Evolving the Structure of Hidden Markov Models," IEEE Transactions on Evolutionary Computation, 2005, accepted.
    • (2005) IEEE Transactions on Evolutionary Computation
  • 11
    • 0034825617 scopus 로고    scopus 로고
    • Optimisation of HMM topology and its model parameters by genttic algorithms
    • S. Kwong, C. Chau, K. Man, and K. Tang, "Optimisation of HMM topology and its model parameters by genttic algorithms," Pattern recognition, vol. 34, pp. 509-522, 2001.
    • (2001) Pattern Recognition , vol.34 , pp. 509-522
    • Kwong, S.1    Chau, C.2    Man, K.3    Tang, K.4
  • 13
    • 84944313315 scopus 로고    scopus 로고
    • Evolving the topology of hidden markov models using evolutionary algorithms
    • R. Thomsen, "Evolving the Topology of Hidden Markov Models Using Evolutionary Algorithms," LNCS, vol. 2439, pp. 861-870, 2002.
    • (2002) LNCS , vol.2439 , pp. 861-870
    • Thomsen, R.1
  • 14
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," in Proceeding of IEEE, vol. 77, no. 2, 1989, pp. 257-286.
    • (1989) Proceeding of IEEE , vol.77 , Issue.2 , pp. 257-286
    • Rabiner, L.R.1
  • 15
    • 0026206264 scopus 로고
    • Hidden Markov models for speech recognition
    • B. Juang and L. Rabiner, "Hidden Markov models for speech recognition," Technometrics, vol. 33, no. 3, pp. 251-272, 1991.
    • (1991) Technometrics , vol.33 , Issue.3 , pp. 251-272
    • Juang, B.1    Rabiner, L.2
  • 18
    • 0035910270 scopus 로고    scopus 로고
    • Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes
    • A. Krogh, B. Larsson, G. von Heijne, and E. Sonnhammer, "Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes," Journal of Molecular Biology, vol. 305, no. 3, pp. 567-580, 2003.
    • (2003) Journal of Molecular Biology , vol.305 , Issue.3 , pp. 567-580
    • Krogh, A.1    Larsson, B.2    Von Heijne, G.3    Sonnhammer, E.4
  • 19
  • 21
    • 16344394781 scopus 로고    scopus 로고
    • SABmark - A benchmark for sequence alignment that covers the entire known fold space
    • I. V. Walle, I. Lasters, and L. Wyns, "SABmark - a benchmark for sequence alignment that covers the entire known fold space," Bioinformatics, vol. 21, no. 7, pp. 1267-1268, 2005.
    • (2005) Bioinformatics , vol.21 , Issue.7 , pp. 1267-1268
    • Walle, I.V.1    Lasters, I.2    Wyns, L.3
  • 22
    • 0020997912 scopus 로고
    • Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features
    • W. Kabsch and C. Sander, "Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features," Biopolymers, vol. 22, pp. 2577-2637, 1983.
    • (1983) Biopolymers , vol.22 , pp. 2577-2637
    • Kabsch, W.1    Sander, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.