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Volumn 80, Issue , 2008, Pages 227-252

Rule extraction from SVM for protein structure prediction

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EID: 38049092147     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-75390-2_10     Document Type: Article
Times cited : (6)

References (51)
  • 2
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2):121-167 (1998).
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C.J.C.1
  • 4
    • 0033562880 scopus 로고    scopus 로고
    • New Methods for accurate prediction of protein secondary structure
    • Chandonia, J.M. and Karplus, M.: New Methods for accurate prediction of protein secondary structure. Proteins (1999) 35, 293-306.
    • (1999) Proteins , vol.35 , pp. 293-306
    • Chandonia, J.M.1    Karplus, M.2
  • 5
    • 0036893269 scopus 로고    scopus 로고
    • Transmembrane helix predictions revisited
    • Chen, C.P., Kernytsky, A. and Rost, B.: Transmembrane helix predictions revisited. Protein Science, vol. 11, (2002), pp. 2774-2791.
    • (2002) Protein Science , vol.11 , pp. 2774-2791
    • Chen, C.P.1    Kernytsky, A.2    Rost, B.3
  • 6
    • 0036776464 scopus 로고    scopus 로고
    • Cho, Y.H., Kim, J.K. and Kim, S.H.: A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications, 23, Issue 3, 1, (2002), 329-342.
    • Cho, Y.H., Kim, J.K. and Kim, S.H.: A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications, Volume 23, Issue 3, 1, (2002), 329-342.
  • 7
    • 0346331362 scopus 로고    scopus 로고
    • Decision Tree based on data envelopment analysis for effective technology commercialization
    • Sohn, S. Y. and Moon, T.H.: Decision Tree based on data envelopment analysis for effective technology commercialization. Expert Systems with Applications, Volume 26, Issue 2, (2004), 279-284.
    • (2004) Expert Systems with Applications , vol.26 , Issue.2 , pp. 279-284
    • Sohn, S.Y.1    Moon, T.H.2
  • 8
    • 0026458378 scopus 로고
    • Amino Acid Substitution Matrices from Protein Blocks
    • Henikoff, S. and Henikoff, J.G.: Amino Acid Substitution Matrices from Protein Blocks. PNAS 89, 10915-10919 (1992).
    • (1992) PNAS , vol.89 , pp. 10915-10919
    • Henikoff, S.1    Henikoff, J.G.2
  • 9
    • 10644246923 scopus 로고    scopus 로고
    • Improved Protein Secondary Structure Prediction Using Support Vector Machine with a New Encoding Scheme and an Advanced Tertiary Classifier
    • Dec
    • Hu, H., Pan, Y., Harrison, R. and Tai, P. C.: Improved Protein Secondary Structure Prediction Using Support Vector Machine with a New Encoding Scheme and an Advanced Tertiary Classifier. IEEE Transactions on NanoBioscience, Vol. 3, No. 4, Dec. 2004, pp. 265-271.
    • (2004) IEEE Transactions on NanoBioscience , vol.3 , Issue.4 , pp. 265-271
    • Hu, H.1    Pan, Y.2    Harrison, R.3    Tai, P.C.4
  • 10
    • 0035957531 scopus 로고    scopus 로고
    • A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach
    • Hua, S. and Sun, Z.: A Novel Method of Protein Secondary Structure Prediction with High Segment Overlap Measure: Support Vector Machine Approach. J. Mol. Biol. (2001) 308: 397-407.
    • (2001) J. Mol. Biol , vol.308 , pp. 397-407
    • Hua, S.1    Sun, Z.2
  • 11
    • 17044421824 scopus 로고    scopus 로고
    • Joachims, T.: SVMlight. http://www.cs.cornell.edu/People/tj/svm_light/ (2002).
    • (2002) SVMlight
    • Joachims, T.1
  • 13
    • 0034274591 scopus 로고    scopus 로고
    • A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty Tree Old and New Classification Algorithm
    • Sept
    • Lim, T.S., Loh, W.Y. and Shih, Y.S.: A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty Tree Old and New Classification Algorithm. Machine Learning, Vol. 40, no. 3, pp. 203-228, Sept. 2000.
    • (2000) Machine Learning , vol.40 , Issue.3 , pp. 203-228
    • Lim, T.S.1    Loh, W.Y.2    Shih, Y.S.3
  • 16
    • 0030643619 scopus 로고    scopus 로고
    • Clustering association rules
    • Lent, B., Swami, A. N. and Widom, J. Clustering association rules. In ICDE, 1997, pages 20-231.
    • (1997) ICDE , pp. 20-231
    • Lent, B.1    Swami, A.N.2    Widom, J.3
  • 17
    • 1542559402 scopus 로고    scopus 로고
    • B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press
    • Noble, W.S.: Kernel Methods in Computational Biology. B. Schoelkopf, K. Tsuda and J.-P. Vert, ed. MIT Press (2004) 71-92.
    • (2004) Kernel Methods in Computational Biology , pp. 71-92
    • Noble, W.S.1
  • 19
    • 0034776419 scopus 로고    scopus 로고
    • Automatic Rule Generation for protein Annotation with the C4.5 Data Mining Algorithm Applied on SWISS-PROT
    • Kretschmann, E., Fleischmann, W. and Apweiler, R.: Automatic Rule Generation for protein Annotation with the C4.5 Data Mining Algorithm Applied on SWISS-PROT. Bioinformatics, (2001), 17(10).
    • (2001) Bioinformatics , vol.17 , Issue.10
    • Kretschmann, E.1    Fleischmann, W.2    Apweiler, R.3
  • 20
    • 38049027502 scopus 로고    scopus 로고
    • Ruinlan, J.R.: C4.5:Programs for Machine Learning. San Mateo, Calif: Morgan Kaufmann, 1993.
    • Ruinlan, J.R.: C4.5:Programs for Machine Learning. San Mateo, Calif: Morgan Kaufmann, 1993.
  • 21
    • 0027291015 scopus 로고
    • Prediction of protein Secondary Structure at Better than 70% Accuracy
    • Rost, B. and Sander, C.: Prediction of protein Secondary Structure at Better than 70% Accuracy. J. Mol. Biol. (1993) 232, 584-599.
    • (1993) J. Mol. Biol , vol.232 , pp. 584-599
    • Rost, B.1    Sander, C.2
  • 23
    • 1842455240 scopus 로고    scopus 로고
    • Bio-support Vector Machines for Computational Proteomics
    • Yang, Z.R. and Chou, K.: Bio-support Vector Machines for Computational Proteomics. Bioinformatics 20(5), 2004.
    • (2004) Bioinformatics , vol.20 , Issue.5
    • Yang, Z.R.1    Chou, K.2
  • 24
    • 27844568170 scopus 로고    scopus 로고
    • Sikder, A.R. and Zomaya, A.Y.: An overview of protein-folding techniques: Issues and perspectives, Int. J. Bioinformatics Research and Applications, 1, issure 1, pp. 121-143, 2005.
    • Sikder, A.R. and Zomaya, A.Y.: An "overview of protein-folding techniques: Issues and perspectives," Int. J. Bioinformatics Research and Applications, Vol. 1, issure 1, pp. 121-143, 2005.
  • 25
    • 27844596815 scopus 로고    scopus 로고
    • Transmembrane segments prediction and understanding using support vector machine and decision tree
    • He, J., Hu, H., Harrison, R., Tai, P.C. and Y. Pan, "Transmembrane segments prediction and understanding using support vector machine and decision tree," Expert Systems with Applications, Special Issue on Intelligent Bioinformatics Systems, vol. 30, pp. 64-72, 2006.
    • (2006) Expert Systems with Applications , vol.30 , pp. 64-72
    • He, J.1    Hu, H.2    Harrison, R.3    Tai, P.C.4    Pan, Y.5
  • 26
    • 0029484103 scopus 로고
    • A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks
    • Andrews, R., Diederich, J. and Tickle, A.: A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks. Knowledge-Based Systems (1995), 8(6), pp. 373-389.
    • (1995) Knowledge-Based Systems , vol.8 , Issue.6 , pp. 373-389
    • Andrews, R.1    Diederich, J.2    Tickle, A.3
  • 27
    • 0032208720 scopus 로고    scopus 로고
    • The Truth will come to light: Directions and Challenges in Extracting the Knowledge Embedded within Trained Artificial Neural Networks
    • Tickle, A., Andrews, R., Mostefa, G. and Diederich, J.: The Truth will come to light: Directions and Challenges in Extracting the Knowledge Embedded within Trained Artificial Neural Networks. IEEE Transactions on Neural Networks, (1998), 9(6), pp. 1057-1068.
    • (1998) IEEE Transactions on Neural Networks , vol.9 , Issue.6 , pp. 1057-1068
    • Tickle, A.1    Andrews, R.2    Mostefa, G.3    Diederich, J.4
  • 29
    • 0036893269 scopus 로고    scopus 로고
    • Transmembrane helix predictions revisited
    • Chen, C.P., Kernytsky, A. and Rost, B.: Transmembrane helix predictions revisited. Protein Science, vol. 11, (2002), pp. 2774-2791.
    • (2002) Protein Science , vol.11 , pp. 2774-2791
    • Chen, C.P.1    Kernytsky, A.2    Rost, B.3
  • 30
    • 85142182105 scopus 로고    scopus 로고
    • Möller, S., Kriventseva, Apweiler, E.: V. and R.: A collection of well characterized integral membrane proteins. Bioinformatics, 16, (2000), pp. 1159-1160.
    • Möller, S., Kriventseva, Apweiler, E.: V. and R.: A collection of well characterized integral membrane proteins. Bioinformatics, vol. 16, (2000), pp. 1159-1160.
  • 31
    • 0033578684 scopus 로고    scopus 로고
    • Protein Secondary Structure Prediction Based on Position-specific Scoring Matrix
    • Jones, D. T.: "Protein Secondary Structure Prediction Based on Position-specific Scoring Matrix," J. Mol. Biol, vol. 292, (1999), pp. 195-202.
    • (1999) J. Mol. Biol , vol.292 , pp. 195-202
    • Jones, D.T.1
  • 34
    • 11344262990 scopus 로고    scopus 로고
    • CPAR: Classification based on Predictive Association Rules
    • presented at, San Fransisco, CA
    • Yin, X. and Han, J. "CPAR: Classification based on Predictive Association Rules," presented at SIAM Int. Conf. on Data Mining (SDM'03), San Fransisco, CA, 2003.
    • (2003) SIAM Int. Conf. on Data Mining (SDM'03)
    • Yin, X.1    Han, J.2
  • 40
    • 38049045788 scopus 로고    scopus 로고
    • Quinlan, J. R. and Cameron-Jones, R. M.: FOIL: A Midterm report, presented at European Conference on Machine Learning (ECML-93), Vienna, Austria, 1993.
    • Quinlan, J. R. and Cameron-Jones, R. M.: FOIL: A Midterm report, presented at European Conference on Machine Learning (ECML-93), Vienna, Austria, 1993.
  • 42
    • 0035812599 scopus 로고    scopus 로고
    • Energetics, stability, and prediction of transmembrane helices
    • Jayasinghe S, H. K. and White S.H.: Energetics, stability, and prediction of transmembrane helices., J. Mol. Biol., vol. 312, pp. 927-934, 2001.
    • (2001) J. Mol. Biol , vol.312 , pp. 927-934
    • Jayasinghe, S.H.K.1    White, S.H.2
  • 45
    • 84943262896 scopus 로고    scopus 로고
    • Lele, S., Golden, B., Ozga, K. and Wasil, E. Clustering Rules Using Empirical Similarity of Support Sets Lecture Notes In Computer Science; 2226 archive, Proceedings of the 4th International Conference on Discovery Science table of contents, 2001, Pages: 447-451.
    • Lele, S., Golden, B., Ozga, K. and Wasil, E. Clustering Rules Using Empirical Similarity of Support Sets Lecture Notes In Computer Science; Vol. 2226 archive, Proceedings of the 4th International Conference on Discovery Science table of contents, 2001, Pages: 447-451.
  • 49
    • 33644982752 scopus 로고    scopus 로고
    • Rule Generation for Protein Secondary Structure Prediction with Support Vector Machines and Decision Tree
    • March
    • He, J. Hu, H. Harrison, R., Tai, P.C. and Pan, Y.: Rule Generation for Protein Secondary Structure Prediction with Support Vector Machines and Decision Tree, IEEE Transactions on NanoBioscience, Vol. 5, No. 1, March 2006, pp. 46-53.
    • (2006) IEEE Transactions on NanoBioscience , vol.5 , Issue.1 , pp. 46-53
    • He, J.1    Hu, H.2    Harrison, R.3    Tai, P.C.4    Pan, Y.5
  • 51
    • 1642327509 scopus 로고    scopus 로고
    • Rule extraction:uSing neural networks or for neural networks?
    • Zhou, Z.-H. Rule extraction:uSing neural networks or for neural networks? Journal of Computer Science and Technology, 2004, 19(2), 249-253.
    • (2004) Journal of Computer Science and Technology , vol.19 , Issue.2 , pp. 249-253
    • Zhou, Z.-H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.