메뉴 건너뛰기




Volumn , Issue PART 2, 2010, Pages 356-358

Protein secondary structure prediction based on multi-SVM ensemble

Author keywords

[No Author keywords available]

Indexed keywords

CROSS-VALIDATION TESTS; DATA SETS; ENSEMBLE NETWORKS; MAJORITY VOTING; PROTEIN SECONDARY-STRUCTURE PREDICTION; RESAMPLES; SECONDARY STRUCTURE PREDICTION; TRAINING DATASET; TWO LAYERS; WINNER TAKE ALLS;

EID: 78649269515     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICIP.2010.5564201     Document Type: Conference Paper
Times cited : (8)

References (26)
  • 1
    • 0034126813 scopus 로고    scopus 로고
    • Protein structure prediction in the post genomic era
    • Jones D T, "Protein structure prediction in the post genomic era". Current Opinion in Structural Biology, 10:371-379,2000
    • (2000) Current Opinion in Structural Biology , vol.10 , pp. 371-379
    • Jones, D.T.1
  • 3
    • 0027291015 scopus 로고
    • Prediction of protein secondary structure at better than 70% accuracy
    • DOI 10.1006/jmbi.1993.1413
    • Rost, B. & Sander, C, "Prediction of secondary structure at better than 70% accuracy," J. Mol Biol, vol, 232, pp. 584-599, 1993. (Pubitemid 23251181)
    • (1993) Journal of Molecular Biology , vol.232 , Issue.2 , pp. 584-599
    • Rost, B.1    Sander, C.2
  • 4
    • 0029984070 scopus 로고    scopus 로고
    • Improving prediction of protein secondary structure suing structured neural networks and multiple sequence alignments
    • Riis, S. K. & Krogh, "A. Improving prediction of protein secondary structure suing structured neural networks and multiple sequence alignments," J. Comput. Biol. vol. 3, pp.163-183, 1996.
    • (1996) J. Comput. Biol. , vol.3 , pp. 163-183
    • Riis, S.K.1    Krogh, A.2
  • 5
    • 0033369033 scopus 로고    scopus 로고
    • Exploiting the past and the future in protein secondary structure prediction
    • Baldi, P., Brunak, S., Frasconi, P., Soda, G. & Pollastri, G, "Exploiting the past and the future in protein secondary structure prediction," Bioinformatics, vol. 15, pp. 937-946, 1999.
    • (1999) Bioinformatics , vol.15 , pp. 937-946
    • Baldi, P.1    Brunak, S.2    Frasconi, P.3    Soda, G.4    Pollastri, G.5
  • 6
    • 33646192301 scopus 로고    scopus 로고
    • Structural bioinformatics prediction of membrane-binding proteins
    • Nitin Bhardwaj, Robert V. Stahelin, Robert E. Langlois, "Structural Bioinformatics Prediction of Membrane-binding Proteins," J. Mol. Biol. Vol. 359, pp. 486-495, 2006.
    • (2006) J. Mol. Biol. , vol.359 , pp. 486-495
    • Bhardwaj, N.1    Stahelin, R.V.2    Langlois, R.E.3
  • 7
    • 0026771388 scopus 로고
    • Hybrid system for protein secondary structure pre diction
    • Zhang, X., Mesirov, J. P. & Waltz, D, "L. Hybrid system for protein secondary structure pre diction," J. Mol. Bio,. Vol. 225, pp. 10490-1063, 1992.
    • (1992) J. Mol. Bio. , vol.225 , pp. 10490-1063
    • Zhang, X.1    Mesirov, J.P.2    Waltz, D.L.3
  • 8
    • 0033106244 scopus 로고    scopus 로고
    • Evaluation and improvement of multiple sequence methods for protein secondary structure prediction
    • Cuff, J. A. & Barton, G. J, "Evaluation and improvement of multiple sequence methods for protein secondary structure prediction," Proteins: Struct. Funct. Genet, vol. 34, pp. 508-519, 1999.
    • (1999) Proteins: Struct. Funct. Genet , vol.34 , pp. 508-519
    • Cuff, J.A.1    Barton, G.J.2
  • 9
    • 28444439947 scopus 로고    scopus 로고
    • Using logitboost classifier to predict protein structural classes
    • Cai, Y.-D., Feng, K.-Y., Lu, W.-C, Chou, K.-C. "Using logitboost classifier to predict protein structural classes," J. Theor. Biol. vol. 238, pp. 172-176,2006.
    • (2006) J. Theor. Biol. , vol.238 , pp. 172-176
    • Cai, Y.-D.1    Feng, K.-Y.2    Lu, W.-C.3    Chou, K.-C.4
  • 10
    • 61649097231 scopus 로고    scopus 로고
    • Structural alphabets for protein structure classification, A comparison study
    • Quan Le, Gianluca Pollastri, and Patrice Koehl, "Structural Alphabets for Protein Structure Classification, A Comparison Study," J. Mol. Biol. vol. 387, pp. 431-450, 2009.
    • (2009) J. Mol. Biol. , vol.387 , pp. 431-450
    • Le, Q.1    Pollastri, G.2    Koehl, P.3
  • 12
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes, C. & Vapnik, V. "Support vector networks," Machine Learning, vol. 20, pp. 273-293. 1995.
    • (1995) Machine Learning , vol.20 , pp. 273-293
    • Cortes, C.1    Vapnik, V.2
  • 16
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • S. Tong, D. Koller, "Support vector machine active learning with applications to text classification," J. Mack Learn, Res. Vol. 2, 2001.
    • (2001) J. Mack Learn, Res. , vol.2
    • Tong, S.1    Koller, D.2
  • 17
    • 0035957531 scopus 로고    scopus 로고
    • A novel method of protein secondary structure prediction with high segment overlap, measure: Support vector machine approach
    • Sujun Hua, Zhirong Sun, "A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap, Measure: Support Vector Machine Approach," J. Mol. Biol. vol. 308, pp.397-407, 2001.
    • (2001) J. Mol. Biol. , vol.308 , pp. 397-407
    • Hua, S.1    Sun, Z.2
  • 18
    • 33847715887 scopus 로고    scopus 로고
    • Prediction of protein secondary structure content using support vector machine
    • etc.
    • Chao Chen, Yuanxin Tian, Xiaoyong Zou, etc. "Prediction of protein secondary structure content using support vector machine," Talanta, vol. 71, pp. 2069-2073, 2007.
    • (2007) Talanta , vol.71 , pp. 2069-2073
    • Chen, C.1    Tian, Y.2    Zou, X.3
  • 19
    • 0742271712 scopus 로고    scopus 로고
    • Combining protein secondary structure prediction models with ensemble methods of optimal complexity
    • etc
    • Yann Guermeura, Gianluca Pollastrib, Andre Elisseeff, etc, "Combining protein secondary structure prediction models with ensemble methods of optimal complexity," Neurocomputing, vol. 56, pp. 305-327, 2004.
    • (2004) Neurocomputing , vol.56 , pp. 305-327
    • Guermeura, Y.1    Pollastrib, G.2    Elisseeff, A.3
  • 21
    • 0031516467 scopus 로고    scopus 로고
    • On combining artificial neural nets
    • March
    • Amanda J. C. Sharkey, "On combining artificial neural nets," Connection Science, Vol. 9, pp. 3-10, March 1997.
    • (1997) Connection Science , vol.9 , pp. 3-10
    • Amanda, J.1    Sharkey, C.2
  • 23
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Leo Breiman, "Bagging predictors," Machine Learning, vol. 24, pp. 123-140, 1996.
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 24
    • 0027291015 scopus 로고
    • Prediction of protein secondary structure at better than 70% accuracy
    • DOI 10.1006/jmbi.1993.1413
    • Rost, B, Sander, C. "Prediction of secondary structure at better than 70% accuracy," J. Mol. Biol. vol. 232, pp. 584-599,1993. (Pubitemid 23251181)
    • (1993) Journal of Molecular Biology , vol.232 , Issue.2 , pp. 584-599
    • Rost, B.1    Sander, C.2
  • 25
    • 0036467068 scopus 로고    scopus 로고
    • Alignments grow, secondary structure prediction improves
    • Dariusz Przybylski, Burkhard Rost, "Alignments Grow, Secondary Structure Prediction Improves," PROTEINS: Structure, Function, and Genetics, vol. 46, pp. 197-205, 2002.
    • (2002) PROTEINS: Structure, Function, and Genetics , vol.46 , pp. 197-205
    • Przybylski, D.1    Rost, B.2
  • 26
    • 55949118135 scopus 로고    scopus 로고
    • A protein secondary structure prediction framework based on the extreme learning
    • Guoren Wang, Yi Zhao, Di Wang, "A protein secondary structure prediction framework based on the Extreme Learning," Machine Neurocomputing, vol. 72, pp. 262-268,2008.
    • (2008) Machine Neurocomputing , vol.72 , pp. 262-268
    • Wang, G.1    Zhao, Y.2    Wang, D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.