Prediction of protein homo-oligomer types by pseudo amino acid composition: Approached with an improved feature extraction and Naive Bayes Feature Fusion

Amino Acids

Volumn 30, Issue 4, 2006, Pages 461-468

  Zhang, S W ^a   Pan, Q ^a   Zhang, H C ^a   Shao, Z C ^a   Shi, J Y ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Homo oligomer; Naive Bayes Feature Fusion; Pseudo amino acid composition; Support vector machine; Weighted auto correlation function

Indexed keywords

OLIGOMER; PROTEIN; PROTEIN SUBUNIT;

ACCURACY; ALGORITHM; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; COMPLEX FORMATION; EXTRACTION; FEASIBILITY STUDY; HYDROPHOBICITY; MACROMOLECULE; OLIGOMERIZATION; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN PROTEIN INTERACTION; PROTEIN QUATERNARY STRUCTURE;

ALGORITHMS; AMINO ACID SEQUENCE; AMINO ACIDS; COMPUTER SIMULATION; DATABASES, FACTUAL; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; HYDROPHOBICITY; PREDICTIVE VALUE OF TESTS; PROTEIN FOLDING; PROTEIN STRUCTURE, QUATERNARY; PROTEINS;

EID: 33745076136     PISSN: 09394451     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00726-006-0263-8     Document Type: Article

References (61)

1. CB Anfisen 1973 Principles that govern the folding of protein chains Science 181 223 230
2. CB Anfinsen E Haber M Sela FH White 1961 The kinetics of the formation of native ribonuclease during oxidation of the reduced polypeptide chain Proc Natl Acad Sci USA 47 1309 1314
3. I Bahar AR Atilgan RL Jernigan B Erman 1997 Understanding the recognition of protein structural classes by amino acid composition Proteins 29 172 185
4. A Bairoch R Apweiler 1996 The SWISS-PROT protein data bank and its new supplement TrEMBL Nucleic Acids Res 24 21 25
5. J Cedano P Aloy JA Pérez-Pons E Querol 1997 Relation between amino acid composition and cellular location of proteins J Mol Biol 266 594 600
6. KC Chou 1988 Review: Low-frequency collective motion in biomacromolecules and its biological functions Biophys Chem 30 3 48
7. KC Chou 1995 A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space Proteins 21 319 344
8. KC Chou 2000a Review: Prediction of protein structural classes and subcellular locations Curr Protein Peptide Sci 1 171 208
9. KC Chou 2000b Prediction of protein subcellular locations by incorporating quasi-sequence-order effect Biochem Biophys Res Commun 278 477 483
10. KC Chou 2001 Prediction of protein cellular attributes using pseudo-amino acid composition Proteins Struct Funct Genet 43 246 255
11. KC Chou 2004a Molecular therapeutic target for type-2 diabetes J Proteome Res 3 1284 1288
12. KC Chou 2004b Insights from modelling three-dimensional structures of the human potassium and sodium channels J Proteome Res 3 856 861
13. KC Chou 2004c Insights from modelling the 3D structure of the extracellular domain of alpha7 nicotinic acetylcholine receptor Biochem Biophys Res Commun 319 433 438
14. KC Chou 2004d Modelling extracellular domains of GABA-A receptors: subtypes 1, 2, 3, and 5 Biochem Biophys Res Commun 316 636 642
15. KC Chou 2004e Review: Structural bioinformatics and its impact to biomedical science Curr Med Chem 11 2105 2134
16. KC Chou 2005 Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes Bioinformatics 21 10 19
17. KC Chou YD Cai 2003a Prediction and classification of protein subcellular location: sequence-order effect and pseudo amino acid composition J Cell Biochem 90 1250 1260 (Addendum: J Cell Biochem 91: 1085 (2004))
18. KC Chou YD Cai 2003b Predicting protein quaternary structure by pseudo amino acid composition Proteins Struct Func Gene 53 282 289
19. KC Chou YD Cai 2003c A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology Biochem Biophys Res Commun 311 743 747
20. KC Chou YD Cai 2004a Predicting enzyme family class in a hybridization space Protein Sci 13 2857 2863
21. KC Chou YD Cai 2004b Predicting subcellular localization of proteins by hybridizing functional domain composition and pseudo-amino acid composition J Cell Biochem 91 1197 1203
22. KC Chou DW Elord 1999 Prediction of membrane protein types and subcellular locations Proteins Struct Funct Genet 34 137 153
23. KC Chou CT Zhang 1994 Predicting protein folding types by distance functions that make allowances for amino acid interactions J Biol Chem 269 22014 22020
24. KC Chou CT Zhang 1995 Review: Prediction of protein structural classes Crit Rev Biochem Mol Biol 30 275 349
25. JL Cornette KB Cease H Margali JL Spouge JA Berzofsky C Delisi 1987 Hydrophobicity scales and computational techniques for detecting amphipathic structures in proteins J Mol Biol 195 659 685
26. O Emanuelsson H Nielsen S Brunak G von Heijne 2000 Predicting subcellular localization of proteins based on their N-terminal amino acid sequence J Mol Biol 300 1005 1016
27. GD Fasman 1976 Handbook of biochemistry and molecular biology 3 CRC Press Boca Raton
28. ZP Feng 2001 Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition Biopolymers 58 491 509
29. Y Gao SH Shao X Xiao YS Ding YS Huang ZD Huang KC Chou 2005 Using pseudo amino acid composition to predict protein subcellular location: approached with Lyapunov index, Bessel function, and Chebyshev filter Amino Acids 28 373 376
30. R Garian 2001 Prediction of quaternary structure from primary structure Bioinformatics 17 551 556
31. F Glase DM Steinberg IA Vakser N Ben-Tal 2001 Residue frequencies and pairing preferences at protein-protein interfaces Proteins Struct Funct Genet 43 89 102
32. SJ Hua ZR Sun 2001 Support vector machine approach for protein subcellular localization prediction Bioinformatics 17 721 728
33. S Jones JM Thornton 1997a Analysis of protein-protein interaction sites using surface patches J Mol Biol 272 121 132
34. S Jones JM Thornton 1997b Prediction of protein-protein interaction sites using patch analysis J Mol Biol 272 133 143
35. LI Kuncheva 2002 Switching between selection and fusion in combining classifiers: an experiment IEEE Trans 32 146 156
36. W Liu KC Chou 1999 Protein secondary structural content prediction Protein Eng 12 1041 1050
37. JL Meek ZL Rossetti 1981 Factors affecting retention and resolution of peptides in HPLC J Chromatogr 211 15 28
38. SM Muskal SH Kim 1992 Predicting protein secondary structure content: a tandem neural network approach J Mol Biol 225 713 727
39. H Nakashima K Nishikawa 1994 Discrimination of intracellular and extracellular proteins using amino acid composition and residuepair frequencies J Mol Biol 238 54 61
40. H Nakashima K Nishikawa T Ooi 1986 The folding type of a protein is relevant to the amino acid composition J Biochem 99 152 162
41. K Oxenoid JJ Chou 2005 The structure of phospholamban pentamer reveals a channel-like architecture in membranes Proc Natl Acad Sci USA 102 10870 10875
42. YX Pan ZZ Zhang ZM Guo GY Feng ZD Huang L He 2003 Application of pseudo amino acid composition for predicting protein subcellular location: stochastic signal processing approach J Protein Chem 22 395 402
43. N Qian TJ Sejnowski 1988 Predicting the secondary structure of globular proteins using neural network models J Mal Dial 202 865 884
44. A Reinhardt T Hubbard 1998 Using neural network for prediction of the subcellular location of proteins Nucleic Acids Res 26 2230 2236
45. B Robson DJ Osguthorpe 1979 Refined models for computer simulation of protein folding. Applications to the study of conserved secondary structure and flexible hinge points during the folding of pancreatic trypsin inhibitor J Mol Biol 132 19 51
46. B Rost C Sander 1993 Prediction of secondary structure at better than 70% accuracy J Mol Biol 232 584 599
47. K Shuichi O Hiroyuki K Minoru 1999 Aaindex: amino acid index database Nucleic Acids Res 27 368 369
48. PH Sneath 1966 Relations between chemical structure and biological activity in peptides J Theor Biol 12 157 195
49. K Tomii M Kanehisa 1996 Analysis of amino acid indices and mutation matrices for sequence comparison and structure prediction of proteins Protein Eng 9 27 36
50. V Vapnik 1995 The nature of statistical learning theory Springer New York
51. V Vapnik 1998 Statistical learning theory Wiley New York
52. M Wang J Yang GP Liu ZJ Xu KC Chou 2004 Weighted-support vector machines for predicting membrane protein types based on pseudo amino acid composition Protein Eng Des Select 17 509 516
53. M Wang J Yang ZJ Xu KC Chou 2005 SLLE for predicting membrane protein types J Theor Biol 232 7 15
54. X Xiao S Shao Y Ding Z Huang X Chen KC Chou 2005a Using cellular automata to generate image representation for biological sequences Amino Acids 28 29 35
55. X Xiao S Shao Y Ding Z Huang Y Huang KC Chou 2005b Using complexity measure factor to predict protein subcellular location Amino Acids 28 57 61
56. X Xiao SH Shao YS Ding ZD Huang KC Chou 2006 Using cellular automata images and pseudo amino acid composition to predict protein sub-cellular location Amino Acids 30 49 54
57. CT Zhang R Zhang 1998 A new quantitative criterion to distinguish between α/β and α + β proteins FEBS Lett 440 153 157
58. SW Zhang P Quan HC Zhang YL Zhang HY Wang 2003 Classification of protein quaternary structure with support vector machine Bioinformatics 19 2390 2396
59. GP Zhou 1998 An intriguing controversy over protein structural class prediction J Protein Chem 17 729 738
60. GP Zhou N Assa-Munt 2001 Some insights into protein structural class prediction Proteins Struct Funct Genet 44 57 59
61. GP Zhou K Doctor 2003 Subcellular location prediction of apoptosis proteins Proteins 50 44 48