γ-Turn types prediction in proteins using the support vector machines

Journal of Theoretical Biology

Volumn 249, Issue 4, 2007, Pages 785-790

  Jahandideh, Samad ^a   Sarvestani, Amir Sabet ^a   Abdolmaleki, Parviz ^a   Jahandideh, Mina ^b   Barfeie, Mahdyar ^a  

^a TARBIAT MODARES UNIVERSITY   (Iran)

^b VALI E ASR UNIVERSITY OF RAFSANJAN   (Iran)

Author keywords

Turn types; Support vector machines (SVMs); Tripeptides

Indexed keywords

TRIPEPTIDE;

ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; PEPTIDE; PROTEIN;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; BETA SHEET; PRIORITY JOURNAL; PROTEIN STRUCTURE; PROTEIN TERTIARY STRUCTURE; SUPPORT VECTOR MACHINE; X RAY CRYSTALLOGRAPHY;

ALGORITHMS; AMINOPEPTIDASES; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; MODELS, CHEMICAL; PROTEIN STRUCTURE, SECONDARY; PROTEINS;

EID: 36248961670     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2007.09.002     Document Type: Article

References (53)

1. Alkorta I., Suarez M.L., Heranz R., Gonalez-Muniz R., and Garsia-Lopez M.T. Similarly study on peptide conformation mimetics. J. Mol. Model 2 (1996) 16-25
2. Bystrov V.F., Portnova S.L., Tsetlin V.I., Ivanov V.T., and Ochinnikov Y.A. Conformational studies of peptide systems. The rotational states of the NH-CH fragment of alanine dipeptides by nuclear magnetic resonance. Tetrahedron 42 (1969) 493-515
3. Cai Y.D. Is it a paradox or misinterpretation. Proteins: Struct. Funct. Genet. 43 (2001) 336-338
4. Cai Y.D., Liu X.J., Xu X.B., and Chou K.C. Prediction of protein structural classes by support vector machines. Comput. Chem. 26 (2002) 293-296
5. Cai Y.D., Liu X.J., Xu X.B., and Chou K.C. Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effect. J. Cell Biochem. 84 (2002) 343-348
6. Cai Y.D., Liu X.J., Xu X.B., and Chou K.C. Support vector machines for predicting the specificity of GalNAc-transferase. Peptides 23 (2002) 205-208
7. Chen C., Zhou X., Tian Y., Zou X., and Cai P. Predicting protein structural class with pseudo-amino acid composition and Support Vector Machine fusion network. Anal. Biochem. 357 (2006) 116-121
8. Chen C., Tian Y.X., Zou X.Y., Cai P.X., and Mo J.Y. Using pseudo-amino acid composition and support vector machine to predict protein structural class. J. Theor. Biol. 243 (2006) 444-448
9. Chou K.C. A novel approach to predicting protein structural classes in a (20-1)-d-amino acid composition space. Proteins: Struct. Funct. Genet. 21 (1995) 319-344
10. Chou K.C. Prediction and classification of α-turn types. Biopolymers 42 (1997) 837-853
11. Chou K.C. Prediction of β-turns. J. Pept. Res. 49 (1997) 120-144
12. Chou K.C. Prediction of tight turns and their types in proteins. Anal. Biochem. 286 (2000) 1-16
13. Chou K.C. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics 21 (2005) 10-19
14. Chou K.C. Prediction of G-protein-coupled receptor classes. J. Proteome Res. 4 (2005) 1413-1418
15. Chou K.C., and Blinn J.R. Classification and prediction of β-turn types. J. Protein Chem. 16 (1997) 575-595
16. Chou K.C., and Cai Y.D. Using functional domain composition and support vector machines for prediction of protein subcellular location. J. Biol. Chem. 277 (2002) 45765-45769
17. Chou K.C., and Elrod D.W. Protein subcellular location prediction. Protein Eng. 12 (1999) 107-118
18. Chou K.C., and Elrod D.W. Bioinformatical analysis of G-protein-coupled receptors. J. Proteome Res. 1 (2002) 429-433
19. Chou K.C., and Elrod D.W. Prediction of enzyme family classes. J. Proteome Res. 2 (2003) 183-190
20. Chou K.C., and Shen H.B. Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization. Biochem. Biophys. Res. Commun. 347 (2006) 150-157
21. Chou K.C., and Shen H.B. Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-nearest neighbor classifiers. J. Proteome Res. 5 (2006) 1888-1897
22. Chou K.C., and Shen H.B. Large-scale predictions of Gram-negative bacterial protein subcellular locations. J. Proteome Res. 5 (2006) 3420-3428
23. Chou K.C., and Shen H.B. Large-scale plant protein subcellular location prediction. J. Cell. Biochem. 100 (2007) 665-678
24. Chou K.C., and Shen H.B. Euk-mPLoc: a fusion classifier for large-scale eukaryotic protein subcellular location prediction by incorporating multiple sites. J. Proteome Res. 6 (2007) 1728-1734
25. Chou K.C., and Shen H.B. Signal-CF: a subsite-coupled and window-fusing approach for predicting signal peptides. Biochem. Biophys. Res. Commun. 357 (2007) 633-640
26. Chou K.C., and Zhang C.T. Review: prediction of protein structural classes. Crit. Rev. Biochem. Mol. Biol. 30 (1995) 275-349
27. Du P., and Li Y. Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence. BMC Bioinformatics 7 (2006) 518
28. Garnier J., Osguthorpe D.J., and Robinson B. Analysis and implications of simple methods for predicting the secondary structure of globular proteins. J. Mol. Biol. 120 (1978) 97-120
29. Gibrat J.F., Garnier J., and Robson B. Further developments of protein secondary structure prediction using information theory. New parameters and consideration of residue pairs. J. Mol. Biol. 198 (1987) 425-443
30. Guruprasad K., and Rajkumar S. Beta-and gamma-turns in proteins revisited: a new set of amino acid turn-type dependent positional preferences and potentials. J. Biosci. 25 2 (2000) 143-156
31. Guruprasad K., Shukla S., Adindla S., and Guruprasad L. Prediction of γ-turns from amino acid sequences. J. Pept. Res. 61 5 (2003) 243-251
32. Jahandideh S., Abdolmaleki P., Jahandideh M., and Barzegari Asadabadi E. Novel two-stage hybrid neural discriminant model for predicting proteins structural classes. Biophys. Chem. 128 1 (2007) 87-93
33. Kaur H., and Raghava G.P.S. An evaluation of β-turn prediction methods. Bioinformatics 18 (2002) 1508-1514
34. Kaur H., and Raghava G.P.S. A neural-network based method for prediction of γ-turns in proteins from multiple sequence alignment. Protein Sci. 12 (2003) 923-929
35. Lin H., and Li Q.Z. Predicting conotoxin superfamily and family by using pseudo amino acid composition and modified Mahalanobis discriminant. Biochem. Biophys. Res. Commun. 354 (2007) 548-551
36. Lin H., and Li Q.Z. Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components. J. Comput. Chem. 28 (2007) 1463-1466
37. Nemethy G., and Printz M.P. The γ-turns, a possible folded conformation of the polypeptide chain comparison with the β-turn. Macromolecules 5 (1972) 755-758
38. Shen H.B., and Chou K.C. Ensemble classifier for protein fold pattern recognition. Bioinformatics 22 (2006) 1717-1722
39. Shen H.B., and Chou K.C. Using ensemble classifier to identify membrane protein types. Amino Acids 32 (2007) 483-488
40. Shen H.B., and Chou K.C. Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins. Protein Eng., Des. Select. 20 (2007) 39-46
41. Shen H.B., and Chou K.C. Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells. Biopolymers 85 (2007) 233-240
42. Shen H.B., and Chou K.C. Hum-mPLoc: an ensemble classifier for large-scale human protein subcellular location prediction by incorporating samples with multiple sites. Biochem. Biophys. Res. Commun. 355 (2007) 1006-1011
43. Shepherd A.J., Gorse D., and Thornton J.M. Prediction of the location and type of β-turn types in proteins using neural networks. Protein Sci. 8 (1999) 1045-1055
44. Valentini G. Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles. Artif. Intell. Med. 26 (2002) 281-304
45. Vapnik V.N. The Nature of Statistical Learning Theory (1995), Springer, Berlin
46. Vapnik V. Statistical Learning Theory (1998), Wiley-Interscience, New York
47. Witten I.H., and Frank E. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (1999), Morgan Kaufmann, San Francisco
48. Zell A., and Mamier G. Neural Network Simulator Version 4.2 (1997), University of Stuttgart, Stuttgart, Germany
49. Zhang Q., Yoon S., and Welsh W.J. Improved method for predicting beta turn using support vector machine. Bioinformatics 21 10 (2005) 2370-2374
50. Zhang S.W., Pan Q., Zhang H.C., Shao Z.C., and Shi J.Y. Prediction protein homo-oligomer types by pseudo amino acid composition: approached with an improved feature extraction and naive Bayes feature fusion. Amino Acids 30 (2006) 461-468
51. Zhou G.P. An intriguing controversy over protein structural class prediction. J. Protein Chem. 17 (1998) 729-738
52. Zhou G.P., and Assa-Munt N. Some insights into protein structural class prediction. Proteins: Struct. Funct. Genet. 44 (2001) 57-59
53. Zhou G.P., and Doctor K. Subcellular location prediction of apoptosis proteins. Proteins: Struct. Funct. Genet. 50 (2003) 44-48