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Volumn 67, Issue 2, 2007, Pages 262-270

Predicting disulfide connectivity patterns

Author keywords

Disulfide bond; Disulfide connectivity pattern; Feature selection; Genetic algorithm; Support vector machine

Indexed keywords

CYSTEINE; DISULFIDE;

EID: 33947429601     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.21309     Document Type: Article
Times cited : (27)

References (25)
  • 1
    • 0034781580 scopus 로고    scopus 로고
    • Prediction of disulfide connectivity in proteins
    • Fariselli P, Casadio R. Prediction of disulfide connectivity in proteins. Bioinformatics 2001;17:957-964.
    • (2001) Bioinformatics , vol.17 , pp. 957-964
    • Fariselli, P.1    Casadio, R.2
  • 2
    • 33947393794 scopus 로고    scopus 로고
    • Fariselli P, Riccobelli P, Casadio R, editors. A neural network-based method for predicting the disulfide connectivity in proteins. In: Damiiani E, Jain LC, Howlett RJ, Ichalkaranje N, editors. Knowledge based intelligent information engineering systems and allied technologies (KES 2002), 1. Amsterdam: IOS Press; 2002.
    • Fariselli P, Riccobelli P, Casadio R, editors. A neural network-based method for predicting the disulfide connectivity in proteins. In: Damiiani E, Jain LC, Howlett RJ, Ichalkaranje N, editors. Knowledge based intelligent information engineering systems and allied technologies (KES 2002), Vol.1. Amsterdam: IOS Press; 2002.
  • 3
    • 1842455284 scopus 로고    scopus 로고
    • Disulfide connectivity prediction using recursive neural networks and evolutionary information
    • Vullo A, Frasconi P. Disulfide connectivity prediction using recursive neural networks and evolutionary information. Bioinformatics 2004;20:653-659.
    • (2004) Bioinformatics , vol.20 , pp. 653-659
    • Vullo, A.1    Frasconi, P.2
  • 4
    • 28944433450 scopus 로고    scopus 로고
    • Advances in neural information processing systems
    • Saul LK, Weiss Y, Bottou L, editors, Cambridge, MA: MIT press;
    • Baldi P, Cheng J, Vullo A. Advances in neural information processing systems. In: Saul LK, Weiss Y, Bottou L, editors. Large-scale prediction of disulfiphide bond connectivity. Cambridge, MA: MIT press; 2005. pp97-104.
    • (2005) Large-scale prediction of disulfiphide bond connectivity , pp. 97-104
    • Baldi, P.1    Cheng, J.2    Vullo, A.3
  • 5
    • 27544440502 scopus 로고    scopus 로고
    • Prediction of disulfide connectivity from protein sequences
    • Chen YC, Hwang JK. Prediction of disulfide connectivity from protein sequences. Proteins 2005;61:507-512.
    • (2005) Proteins , vol.61 , pp. 507-512
    • Chen, Y.C.1    Hwang, J.K.2
  • 6
    • 31944444347 scopus 로고    scopus 로고
    • Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching
    • Cheng J, Saigo H, Baldi P. Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching. Proteins 2006;62:617-629.
    • (2006) Proteins , vol.62 , pp. 617-629
    • Cheng, J.1    Saigo, H.2    Baldi, P.3
  • 8
    • 0041819762 scopus 로고    scopus 로고
    • Relationship between protein structures and disulfide-bonding patterns
    • Chuang CC, Chen CY, Yang JM, Lyu PC, Hwang JK. Relationship between protein structures and disulfide-bonding patterns. Proteins 2003;53:1-5.
    • (2003) Proteins , vol.53 , pp. 1-5
    • Chuang, C.C.1    Chen, C.Y.2    Yang, J.M.3    Lyu, P.C.4    Hwang, J.K.5
  • 9
    • 0346493041 scopus 로고    scopus 로고
    • A novel database of disulfide patterns and its application to the discovery of distantly related homologs
    • van Vlijmen HW, Gupta A, Narasimhan LS, Singh J. A novel database of disulfide patterns and its application to the discovery of distantly related homologs. J Mol Biol 2004;335:1083-1092.
    • (2004) J Mol Biol , vol.335 , pp. 1083-1092
    • van Vlijmen, H.W.1    Gupta, A.2    Narasimhan, L.S.3    Singh, J.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, 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
  • 12
    • 0037341893 scopus 로고    scopus 로고
    • Fine-grained protein fold assignment by support vector machines using generalized n-peptide coding schemes and jury voting from multiple-parameter sets
    • Yu CS, Wang JY, Yang JM, Lyu PC, Lin CJ, Hwang JK. Fine-grained protein fold assignment by support vector machines using generalized n-peptide coding schemes and jury voting from multiple-parameter sets. Proteins 2003;50:531-536.
    • (2003) Proteins , vol.50 , pp. 531-536
    • Yu, C.S.1    Wang, J.Y.2    Yang, J.M.3    Lyu, P.C.4    Lin, C.J.5    Hwang, J.K.6
  • 13
    • 2542586190 scopus 로고    scopus 로고
    • Prediction of the bonding states of cysteines using the support vector machines based on multiple feature vectors and cysteine state sequences
    • Chen YC, Lin YS, Lin CJ, Hwang JK. Prediction of the bonding states of cysteines using the support vector machines based on multiple feature vectors and cysteine state sequences. Proteins 2004;55:1036-1042.
    • (2004) Proteins , vol.55 , pp. 1036-1042
    • Chen, Y.C.1    Lin, Y.S.2    Lin, C.J.3    Hwang, J.K.4
  • 14
    • 1942505330 scopus 로고    scopus 로고
    • Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions
    • Yu CS, Lin CJ, Hwang JK. Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci 2004;13:1402-1406.
    • (2004) Protein Sci , vol.13 , pp. 1402-1406
    • Yu, C.S.1    Lin, C.J.2    Hwang, J.K.3
  • 15
    • 18844375632 scopus 로고    scopus 로고
    • Computation of conformational entropy from protein sequences using the machine-learning method-application to the study of the relationship between structural conservation and local structural stability
    • Huang SW, Hwang JK. Computation of conformational entropy from protein sequences using the machine-learning method-application to the study of the relationship between structural conservation and local structural stability. Proteins 2005;59: 802-809.
    • (2005) Proteins , vol.59 , pp. 802-809
    • Huang, S.W.1    Hwang, J.K.2
  • 16
    • 29244465822 scopus 로고    scopus 로고
    • An SVM-based system for predicting protein sub-nuclear localizations
    • Lei Z, Dai Y. An SVM-based system for predicting protein sub-nuclear localizations. BMC Bioinformatics 2005;6:291.
    • (2005) BMC Bioinformatics , vol.6 , pp. 291
    • Lei, Z.1    Dai, Y.2
  • 18
    • 0000222692 scopus 로고    scopus 로고
    • Formulations of support vector machines: A note from an optimization point of view
    • Lin C-J. Formulations of support vector machines: a note from an optimization point of view. Neural Comput 2001;13: 307-317.
    • (2001) Neural Comput , vol.13 , pp. 307-317
    • Lin, C.-J.1
  • 19
    • 33947371051 scopus 로고    scopus 로고
    • Chang C-C, Lin C-J. LIBSVM v. 2.81: a library for support vector machines. 2005. Available athttp://www.csie.ntu.edu.tw/~cjlin/ libsvm
    • Chang C-C, Lin C-J. LIBSVM v. 2.81: a library for support vector machines. 2005. Available athttp://www.csie.ntu.edu.tw/~cjlin/ libsvm
  • 20
    • 0037382208 scopus 로고    scopus 로고
    • Evaluation of simple performance measures for tuning SVM hyperparameters
    • Duan K, Keerthi SS, Poo AN. Evaluation of simple performance measures for tuning SVM hyperparameters. Neurocomputing 2003;51:41-59.
    • (2003) Neurocomputing , vol.51 , pp. 41-59
    • Duan, K.1    Keerthi, S.S.2    Poo, A.N.3
  • 21
    • 0022631926 scopus 로고
    • The folding type of a protein is relevant to the amino acid composition
    • Nakashima H, Nishikawa K, Ooi T. The folding type of a protein is relevant to the amino acid composition. J Biochem 1986;99:152-162.
    • (1986) J Biochem , vol.99 , pp. 152-162
    • Nakashima, H.1    Nishikawa, K.2    Ooi, T.3
  • 22
    • 0034843744 scopus 로고    scopus 로고
    • Support vector machine approach for protein subcellular localization prediction
    • Hua S, Sun Z. Support vector machine approach for protein subcellular localization prediction. Bioinformatics 2001;17:721-728.
    • (2001) Bioinformatics , vol.17 , pp. 721-728
    • Hua, S.1    Sun, Z.2
  • 24
    • 0033957834 scopus 로고    scopus 로고
    • The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000
    • Bairoch A, Apweiler R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res 2000;28:45-48.
    • (2000) Nucleic Acids Res , vol.28 , pp. 45-48
    • Bairoch, A.1    Apweiler, R.2
  • 25
    • 28944438120 scopus 로고    scopus 로고
    • Improving disulfide connectivity prediction with sequential distance between oxidized cysteines
    • Tsai CH, Chen BJ, Chan CH, Liu HL, Kao CY. Improving disulfide connectivity prediction with sequential distance between oxidized cysteines. Bioinformatics 2005;21:4416-4419.
    • (2005) Bioinformatics , vol.21 , pp. 4416-4419
    • Tsai, C.H.1    Chen, B.J.2    Chan, C.H.3    Liu, H.L.4    Kao, C.Y.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.