Predicting subchloroplast locations of proteins based on the general form of Chou's pseudo amino acid composition: Approached from optimal tripeptide composition

International Journal of Biomathematics

Volumn 6, Issue 2, 2013, Pages

  Lin, Hao ^a   Ding, Chen ^a   Yuan, Lu Feng ^a   Chen, Wei ^b   Ding, Hui ^a   Li, Zi Qiang ^c   Guo, Feng Biao ^a   Huang, Jian ^a   Rao, Ni Ni ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b HEBEI UNITED UNIVERSITY   (China)

^c SICHUAN AGRICULTURAL UNIVERSITY   (China)

Author keywords

binomial distribution; Subchloroplast localization; support vector machine; tripeptide

Indexed keywords

EID: 84876241526     PISSN: 17935245     EISSN: 17937159     Source Type: Journal    
DOI: 10.1142/S1793524513500034     Document Type: Article

References (83)

1. S. Anishetty, G. Pennathur and R. Anishetty, Tripeptide analysis of protein structures, BMC Struct. Biol. 2 (2002) 9.
2. N. A. Campbell, B. Williamson and R. J. Heyden, Biology: Exploring Life (Pearson Prentice Hall, Boston, MA, 2006).
3. C. Chen, L. Chen, X. Zou and P. Cai, Prediction of protein secondary structure content by using the concept of Chou's pseudo amino acid composition and support vector machine, Protein Peptide Lett. 16(1) (2009) 27-31.
4. Y. L. Chen and Q. Z. Li, Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo amino acid composition, J. Theor. Biol. 248(2) (2007) 377-381.
5. Y. L. Chen and Q. Z. Li, Prediction of the subcellular location of apoptosis proteins, J. Theor. Biol. 245(4) (2007) 775-783.
6. K. C. Chou, Prediction of protein cellular attributes using pseudo amino acid composition, Proteins 43(3) (2001) 246-255.
7. K. C. Chou, Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes, Bioinformatics 21(1) (2005) 10-19.
8. K. C. Chou, Pseudo amino acid composition and its applications in bioinformatics, proteomics and system biology Curr. Proteomics 6(4) (2009) 262-274.
9. K. C. Chou, Some remarks on protein attribute prediction and pseudo amino acid composition (50th anniversary year review), J. Theor. Biol. 273 (2011) 236-247.
10. K. C. Chou and H. B. Shen, Cell-PLoc: A package of web-servers for predicting subcellular localization of proteins in various organisms (updated version: Cell-PLoc 2.0: An improved package of web-servers for predicting subcellular localization of proteins in various organisms, Nat. Sci. 2(10) (2010) 1090-1103), Nat. Protoc. 3(1) (2008) 153-162.
11. K. C. Chou and H. B. Shen, Review: Recent advances in developing web-servers for predicting protein attributes, Nat. Sci. 2 (2009) 63-92.
12. K. C. Chou and H. B. Shen, A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0, PLoS ONE 5(4) (2010) e9931.
13. K. C. Chou and H. B. Shen, Plant-mPLoc: A top-down strategy to augment the power for predicting plant protein subcellular localization, PLoS ONE 5(6) (2010) e11335.
14. K. C. Chou, Z. C. Wu and X. Xiao, iLoc-Euk: A multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins, PLoS ONE 6(3) (2011) e18258.
15. K. C. Chou, Z. C. Wu and X. Xiao, iLoc-Hum: Using accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites, Molec. Biosyst. 8(2) (2012) 629-641.
16. K. C. Chou and C. T. Zhang, Review: Prediction of protein structural classes, Crit. Rev. Biochem. Molec. Biol. 30(4) (1995) 275-349.
17. H. Ding, L. Liu, F. B. Guo, J. Huang and H. Lin, Identify Golgi protein types with modified Mahalanobis discriminant algorithm and pseudo amino acid composition, Protein Peptide Lett. 18(1) (2011) 58-63.
18. H. Ding, L. F. Luo and H. Lin, Prediction of cell wall lytic enzymes using Chou's amphiphilic pseudo amino acid composition, Protein Peptide Lett. 16(4) (2009) 351-355.
19. Y. S. Ding and T. L. Zhang, Using Chou's pseudo amino acid composition to predict subcellular localization of apoptosis proteins: An approach with immune genetic algorithm-based ensemble classifier, Pattern Recogn. Lett. 29(13) (2008) 1887-1892.
20. P. Du, S. Cao and Y. Li, SubChlo: Predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ETKNN) algorithm, J. Theor. Biol. 261(2) (2009) 330-335.
21. O. Emanuelsson, H. Nielsen and G. von Heijne, ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites, Protein Sci. 8 (1999) 978-984.
22. M. Esmaeili, H. Mohabatkar and S. Mohsenzadeh, Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses, J. Theor. Biol. 263(2) (2010) 203-209.
23. R. E. Fan, P. H. Chen and C. J. Lin, Working set selection using the second order information for training SVM, J. Mach. Learn. Res. 6 (2005) 1889-1918.
24. Y. Fang, Y. Guo, Y. Feng and M. Li, Predicting DNA-binding proteins: Approached from Chou's pseudo amino acid composition and other specific sequence features, Amino Acids 34(1) (2008) 103-109.
25. Y. Feng and L. Luo, Use of tetrapeptide signals for protein secondary-structure prediction, Amino Acids 35(3) (2008) 607-614.
26. D. N. Georgiou, T. E. Karakasidis, J. J. Nieto and A. Torres, Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition, J. Theor. Biol. 257(1) (2009) 17-26.
27. Q. Gu, Y. S. Ding and T. L. Zhang, Prediction of G-protein-coupled receptor classes in low homology using Chou's pseudo amino acid composition with approximate entropy and hydrophobicity patterns, Protein Peptide Lett. 17(5) (2010) 559-567.
28. J. Guo, N. Rao, G. Liu, Y. Yang and G. Wang, Predicting protein folding rates using the concept of Chou's pseudo amino acid composition, J. Comput. Chem. 32(8) (2011) 1612-1617.
29. J. Hu and X. Yan, BS-KNN: An effective algorithm for predicting protein subchloroplast localization, Evol. Bioinform. Online 8 (2012) 79-87.
30. L. Hu, L. Zheng, Z. Wang, B. Li and L. Liu, Using pseudo amino acid composition to predict protease families by incorporating a series of protein biological features, Protein Peptide Lett. 18(6) (2011) 552-558.
31. T. Huang, L. Chen, Y. D. Cai and K. C. Chou, Classification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional property, PLoS ONE 6(9) (2011) e25297.
32. X. Jiang, R. Wei, T. L. Zhang and Q. Gu, Using the concept of Chou's pseudo amino acid composition to predict apoptosis proteins subcellular location: An approach by approximate entropy, Protein Peptide Lett. 15(4) (2008) 392-396.
33. X. Jiang, R. Wei, Y. Zhao and T. Zhang, Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location, Amino Acids 34(4) (2008) 669-675.
34. Y. Jin, B. Niu, K. Y. Feng, W. C. Lu, Y. D. Cai and G. Z. Li, Predicting subcellular localization with AdaBoost learner, Protein Peptide Lett. 15(3) (2008) 286-289.
35. K. K. Kandaswamy, G. Pugalenthi, S. Moller, E. Hartmann, K. U. Kalies, P. N. Suganthan and T. Martine, Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition, Protein Peptide Lett. 17(12) (2010) 1473-1479.
36. F. M. Li and Q. Z. Li, Predicting protein subcellular location using Chou's pseudo amino acid composition and improved hybrid approach, Protein Peptide Lett. 15(6) (2008) 612-616.
37. Z. C. Li, X. B. Zhou, Z. Dai and X. Y. Zou, Prediction of protein structural classes by Chou's pseudo amino acid composition: Approached using continuous wavelet transform and principal component analysis, Amino Acids 37(2) (2009) 415-425.
38. B. Liao, J. B. Jiang, Q. G. Zeng and W. Zhu, Predicting apoptosis protein subcellular location with PseAAC by incorporating tripeptide composition, Protein Peptide Lett. 18(11) (2011) 1086-1092.
39. H. Lin, The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition, J. Theor. Biol. 252(2) (2008) 350-356.
40. H. Lin and H. Ding, Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition, J. Theor. Biol. 269(1) (2011) 64-69.
41. H. Lin, H. Ding, F. B. Guo, A. Y. Zhang and J. Huang, Predicting subcellular localization of mycobacterial proteins by using Chou's pseudo amino acid composition, Protein Peptide Lett. 15(7) (2008) 739-744.
42. H. Lin and Q. Z. Li, Using pseudo amino acid composition to predict protein structural class: Approached by incorporating 400 dipeptide components, J. Comput Chem. 28(9) (2007) 1463-1466.
43. J. Lin and Y. Wang, Using a novel AdaBoost algorithm and Chou's pseudo amino acid composition for predicting protein subcellular localization, Protein Peptide Lett. 18(12) (2011) 1219-1225.
44. H. Lin, H. Wang, H. Ding, Y. L. Chen and Q. Z. Li, Prediction of subcellular localization of apoptosis protein using Chou's pseudo amino acid composition, Acta Biotheor. 57(3) (2009) 321-330.
45. T. Liu, X. Zheng, C. Wang and J. Wang, Prediction of subcellular location of apoptosis proteins using pseudo amino acid composition: An approach from autocovariance transformation, Protein Peptide Lett. 17(10) (2010) 1263-1269.
46. J. Ma and H. Gu, A novel method for predicting protein subcellular localization based on pseudo amino acid composition, BMB Rep. 43(10) (2010) 670-676.
47. S. Mei, Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization, J. Theor. Biol. 293 (2012) 121-130.
48. H. Mohabatkar, Prediction of cyclin proteins using Chou's pseudo amino acid composition, Protein Peptide Lett. 17(10) (2010) 1207-1214.
49. H. Mohabatkar, B. M. Mohammad and A. Esmaeili, Prediction of GABA(A) receptor proteins using the concept of Chou's pseudo-amino acid composition and support vector machine, J. Theor. Biol. 281(1) (2011) 18-23.
50. R. Nair and B. Rost, Sequence conserved for subcellular localization, Protein Sci. 11(12) (2002) 2836-2847.
51. L. Nanni and A. Lumini, Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization, Amino Acids 34(4) (2008) 653-660.
52. L. Nanni, A. Lumini, D. Gupta and A. Garg, Identifying bacterial virulent proteins by fusing a set of classifiers based on variants of Chou's pseudo amino acid composition and on evolutionary information, IEEE/ACM Trans. Comput. Biol. Bioinform. 9 (2012) 467-475.
53. J. D. Qiu, J. H. Huang, R. P. Liang and X. Q. Lu, Prediction of G-protein-coupled receptor classes based on the concept of Chou's pseudo amino acid composition: An approach from discrete wavelet transform, Anal. Biochem. 390(1) (2009) 68-73.
54. J. D. Qiu, J. H. Huang, S. P. Shi and R. P. Liang, Using the concept of Chou's pseudo amino acid composition to predict enzyme family classes: An approach with support vector machine based on discrete wavelet transform, Protein Peptide Lett. 17(6) (2010) 715-722.
55. J. D. Qiu, S. B. Suo, X. Y. Sun, S. P. Shi and R. P. Liang, OligoPred: A web-server for predicting homo-oligomeric proteins by incorporating discrete wavelet transform into Chou's pseudo amino acid composition, J. Molec. Graph Model. 30 (2011) 129-134.
56. S. S. Sahu and G. Panda, A novel feature representation method based on Chou's pseudo amino acid composition for protein structural class prediction, Comput. Biol. Chem. 34(5-6) (2010) 320-327.
57. H. B. Shen and K. C. Chou, Gpos-mPLoc: A top-down approach to improve the quality of predicting subcellular localization of Gram-positive bacterial proteins, Protein Peptide Lett. 16(12) (2009) 1478-1484.
58. S. P. Shi, J. D. Qiu, X. Y. Sun, J. H. Huang, S. Y. Huang, S. B. Suo, R. P, Liang and L. Zhang, Identify submitochondria and subchloroplast locations with pseudo amino acid composition: Approach from the strategy of discrete wavelet transform feature extraction, Biochim. Biophys. Acta 1813(3) (2011) 424-430.
59. R. Shi and C. Xu, Prediction of rat protein subcellular localization with pseudo amino acid composition based on multiple sequential features, Protein Peptide Lett. 18(6) (2011) 625-633.
60. The UniProt Consortium, Ongoing and future developments at the Universal Protein Resource, Nucleic Acids Res. 39 (2011) D214-D219.
61. C. W. Tung, C. Liaw, S. J. Ho and S. Y. Ho, Prediction of protein subchloroplast locations using random forests, World Acad. Sci. Engrg. Tech. 65 (2010) 903-907.
62. P. Ung and D. A. Winkler, Tripeptide motifs in biology: Targets for peptidomimetic design, J. Med. Chem. 54(5) (2011) 111-1125.
63. G.Wang and R. L. Dunbrack, Jr., PISCES: Recent improvements to a PDB sequence culling server, Nucleic Acids Res. 33 (2005) W94-W98.
64. W. Wang, X. B. Geng, Y. Dou, T. Liu and X. Zheng, Predicting protein subcellular localization by pseudo amino acid composition with a segment-weighted and featurescombined approach, Protein Peptide Lett. 18(5) (2011) 480-487.
65. K.Wang, L. L. Hu, X. H. Shi, Y. S. Dong, H. P. Li and T. Q. Wen, PSCL: Predicting protein subcellular localization based on optimal functional domains, Protein Peptide Lett. 19(1) (2012) 15-22.
66. Y. C. Wang, X. B. Wang, Z. X. Yang and N. Y. Deng, Prediction of enzyme subfamily class via pseudo amino acid composition by incorporating the conjoint triad feature, Protein Peptide Lett. 17(11) (2010) 1441-1449.
67. T. Wang, J. Yang, H. B. Shen and K. C. Chou, Predicting membrane protein types by the LLDA algorithm, Protein Peptide Lett. 15(9) (2008) 915-921.
68. Z. C. Wu, X. Xiao and K. C. Chou, iLoc-Plant: A multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites, Molec. BioSyst. 7(12) (2011) 3287-3297.
69. Z. C. Wu, X. Xiao and K. C. Chou, iLoc-Gpos: A multi-layer classifier for predicting the subcellular localization of singleplex and multiplex gram-positive bacterial proteins, Protein Peptide Lett. 19(1) (2012) 4-14.
70. X. Xiao, Z. C. Wu and K. C. Chou, iLoc-Virus: A multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites, J. Theor. Biol. 284(1) (2011) 42-51.
71. J. B. Yin, Y. X. Fan and H. B. Shen, Conotoxin superfamily prediction using diffusion maps dimensionality reduction and subspace classifier, Curr. Protein Peptide Sci. 12(6) (2011) 580-588.
72. C. S. Yu, Y. C. Chen, C. H. Lu and J. K. Hwang, Prediction of protein subcellular localization, Proteins 64(3) (2006) 643-651.
73. L. Yu,Y. Guo, Y. Li,G. Li, M. Li, J. Luo,W. Xiong andW.Qin, SecretP: Identifying bacterial secreted proteins by fusing new features into Chou's pseudo-amino acid composition, J. Theor. Biol. 267(1) (2010) 1-6.
74. P. Zakeri, B. Moshiri andM. Sadeghi, Prediction of protein submitochondria locations based on data fusion of various features of sequences, J. Theor. Biol. 269(1) (2011) 208-216.
75. Y. H. Zeng, Y. Z. Guo, R. Q. Xiao, L. Yang, L. Z. Yu and M. L. Li, Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on autocovariance approach, J. Theor. Biol. 259(2) (2009) 366-372.
76. S. W. Zhang, W. Chen, F. Yang and Q. Pan, Using Chou's pseudo amino acid composition to predict protein quaternary structure: A sequence-segmented PseAAC approach, Amino Acids 35(3) (2008) 591-598.
77. G. Y. Zhang and B. S. Fang, Predicting the cofactors of oxidoreductases based on amino acid composition distribution and Chou's amphiphilic pseudo amino acid composition, J. Theor. Biol. 253(2) (2008) 310-315.
78. G. Y. Zhang, H. C. Li, J. Q. Gao and B. S. Fang, Predicting lipase types by improved Chou's pseudo amino acid composition, Protein Peptide Lett. 15(10) (2008) 1132-1137.
79. L. Zhang, B. Liao, D. Li and W. Zhu, A novel representation for apoptosis protein subcellular localization prediction using support vector machine, J. Theor. Biol. 259(2) (2009) 361-365.
80. S. W. Zhang, Y. L. Zhang, H. F. Yang, C. H. Zhao and Q. Pan, Using the concept of Chou's pseudo amino acid composition to predict protein subcellular localization: An approach by incorporating evolutionary information and von Neumann entropies, Amino Acids 34(4) (2008) 565-572.
81. Z. L. Zheng, L. Guo, J. Jia, C. M. Xie, W. C. Zeng and J. Yang, Compressed learning and its applications to subcellular localization, Protein Peptide Lett. 18(9) (2011) 925-934.
82. X. B. Zhou, C. Chen, Z. C. Li and X. Y. Zou, Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes, J. Theor. Biol. 248(3) (2007) 546-551.
83. D. Zou, Z. He, J. He and Y. Xia, Supersecondary structure prediction using Chou's pseudo amino acid composition, J. Comput. Chem. 32(2) (2011) 271-278.