Prediction of methylation sites using the composition of K-spaced amino acid pairs

Protein and Peptide Letters

Volumn 20, Issue 8, 2013, Pages 911-917

  Zhang, Wenyi ^a   Xu, Xin ^a   Yin, Minghao ^a   Luo, Na ^a   Zhang, Jingbo ^a   Wang, Jianan ^a  

^a NORTHEAST NORMAL UNIVERSITY   (China)

Author keywords

CKSAAP Methsite SVM; Methylation sites; Performance

Indexed keywords

ARGININE; LYSINE; AMINO ACID; PROTEIN;

ACCURACY; ALGORITHM; AMINO ACID ANALYSIS; AMINO ACID SEQUENCE; ANALYTIC METHOD; ARTICLE; COMPOSITION OF K SPACED AMINO ACID PAIR; CONTROLLED STUDY; CORRELATION COEFFICIENT; INTERMETHOD COMPARISON; MATHEMATICAL PARAMETERS; MATHEW CORRELATION COEFFICIENT; METHYLATION SITE; ONLINE SYSTEM; PREDICTION; PREDICTIVE VALUE; PROTEIN METHYLATION; PROTEIN MOTIF; PROTEIN STRUCTURE; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; WINDOW SIZE; BIOLOGY; CHEMISTRY; METABOLISM; METHYLATION; PROTEIN PROCESSING;

AMINO ACIDS; ARGININE; COMPUTATIONAL BIOLOGY; LYSINE; METHYLATION; PROTEIN PROCESSING, POST-TRANSLATIONAL; PROTEINS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINES;

EID: 84882386563     PISSN: 09298665     EISSN: None     Source Type: Journal    
DOI: 10.2174/0929866511320080008     Document Type: Article

References (51)

1. Mann, M.; Jensen, O.N. Proteomic analysis of post-Translational modifications. Nat. Biotechnol., 2003, 21, 255-261. doi:10.1038/nbt0303-255.
2. Shao, J.L; Xu, D; Tsai,S.N; Wang,Y.F; Ngai,S.M. Computational identification of Protein Methylation Sites through Bi-Profile Bays Feature Extraction. PLos ONE, 2009, 3, 1-7.
3. Xie, B.; Invernizzi, CF.; Richard, S.; Wainberg, MA. Arginine methylation of the human immunodeficiency virus type 1 Tat protein by PRMT6 negatively affects Tat Interactions with both cyclin T1 and the Tat transactivation region. J. Virol., 2007, 81, 4226-4234.
4. Cheng, D.; Cote, J.; Shaaban, S.; Bedford, MT. The arginine methyltransferase CARM1 regulates the coupling of transcription and mRNA processing. Mol. Cell, 2007, 25, 71-83.
5. Torres-Padilla, ME.; Parifitt, DE.; Kouzarides, T.; Zernicka-Coetz, M. Histone arginine methylation regulates pluripotency in the early mouse embryo. Nature, 2007, 445, 214-218.
6. Barski, A; Cuddapah, S.; Cui, K.; Roh, T.Y.; Schones, D.E.; Wang, Z.; Wei, G.; Chepelev, I.; Zhao, K. High-resolution profiling of histone methylations in the human genome. Cell, 2007, 129, 823-837.
7. Porras-Yakushi, T.R.; Whitelegge, J.P.; Clarke, S. Yeast ribosomal/cytochrome c SET domain methyltransferase subfamily: identification of Rp123ab methylation sites and recognition motifs. J. Biol. Chem., 2007, 282, 12368-12376.
8. Chen, H.; Xue, Y.; Huang, N.; Yao, X.; Sun, Z. MeMo: a web tool for prediction of protein methylation modifications. Nucleic Acid Res., 2006, 34, W249-253.
9. Hu, L.L.; Li, Z.; Wang, K.; Niu, S.; Shi, X.H.; Cai, Y.D.; Li, H.P. Prediction and Analysis of Protein Methylarginine and Methyllysine Based on Multisequence features. Biopolymers, 2011, 95(11), 763-771.
10. Chou, K.C. Some remarks on protein attribute prediction and pseudo amino acid composition (50th Anniversary Year Review). J. Theor. Biol., 2011, 273, 236-247.
11. Wu, Z.C.; Xiao, X.; Chou, K.C. iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites. Mol. Biosyst., 2011, 7, 3287-3297.
12. Xiao, X.; Wu, Z.C.; Chou, K.C. iLoc-Virus: A multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites. J. Theor. Biol., 2011, 284, 42-51.
13. Chou, K.C.; Wu, Z.C.; Xiao, X. iLoc-Euk: A Multi-Label Classifier for Predicting the Subcellular Localization of Singleplex and Multiplex Eukaryotic Proteins. PLoS ONE, 2011, 6, e18258.
14. Wu, Z.C.; Xiao, X.; Chou, K.C. iLoc-Gpos: A Multi-Layer Classifier for Predicting the Subcellular Localization of Singleplex and Multiplex Gram-Positive Bacterial Proteins. Protein Pept. Lett., 2012, 19, 4-14.
15. Xiao, X.; Wang, P.; Chou, K.C. GPCR.-2L: Predicting G proteincoupled receptors and their types by hybridizing two different modes of pseudo amino acid compositions. Mol. Biosyst., 2011, 7, 911-919.
16. Chou, K.C.; Wu, Z.C.; Xiao, X. iLoc-Hum: Using accumulationlabel scale to predict subcellular locations of human proteins with both single and multiple sites. Mol. Biosyst., 2012, 8, 629-641.
17. Chen, W.; Lin, H.; Feng, P.M.; Ding, C.; Zuo, Y.C.; Chou, K.C. iNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical Properties. PLoS ONE, 2012, 7, e47843.
18. Chen, Z; Chen, Y.Z; Wang, X.F; Wang, C; Yan, R.X; Zhang, Z. Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs. PLos ONE, 2011, 7, 1-8.
19. Wang, X.B; Wu, L.Y; Wang, Y.C; Deng, N.Y. Prediction of palmitoylation sites using the composition of k-spaced amino acid pairs. Protein Eng. Des. Sel., 2009, 22(11), 707-712.
20. Chen, Y.Z; Tang, Y.R; Sheng, Z.Y; Zhang, Z. Prediction of mucintype O.-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs. BMC Bioinformatics, 2008, 9, 101. dio:10.1186/1471-2105-9-101.
21. Chou, K.C.; Shen, H.B. Review: recent advances in developing web-servers for predicting protein attributes. Natural Science, 2009, 2, 63-92; doi: 10.4236/ns.2009.12011 (openly accessible at http://www.scirp.org/journal/NS/)
22. UniProt. Available online: http://www.uniprot.org/(accessed on 15 June 2012).
23. Chou, K.C. Some remarks on protein attribute prediction and pseudo amino acid composition (50th Anniversary Year Review). J. Theor. Biol., 2011, 273, 236-247.
24. Chou, K.C. Prediction of protein cellular attributes using pseudo amino acid composition. Proteins: Structure, Function, and Genetics (Erratum: ibid., 2001, Vol.44, 60), 2001, 43, 246-255.
25. Chou, K.C. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics, 2005, 21, 10-19.
26. Zhao, X.W.; Ma, Z.Q.; Yin, M.H. Using Support Vector Machine and Evolutionary Profiles to Predict Antifreeze Protein Sequence. Int. J. Mol. Sci., 2012, 13, 2196-2207. doi: 10.3390/ijms 13022196.
27. Zhao, X.W.; Ma, Z.Q.; Yin, M.H. Predicting Protein-Protein Interactions by combing Various Sequence Derived Features into the General Form of Chou's Pseudo Amino Acid Composition. Protein Pept. Lett., 2012, 19(5), 492-500.
28. Chang, C.C.; Lin, C.J. LIBSVM: A library for support vector machine. 2001, doi:10.1145/1961189.196119.5
29. LIBSVM. Available online: http://www.csite.ntu.edu.tw/sjlin/libsvm (accessed on 23 June 2012).
30. Zhao, X.W.; Li, X.T.; Ma, Z.Q.; Yin, M.H. Prediction of Lysine Ubiquitylation with Ensemble Classifier and Feature Selection. Int. J. Mol. Sci., 2011, 12, 8347-8461. doi:10.3390/ijms12128347.
31. Chou, K.C.; Zhang, C.T. Review: Prediction of Protein Structural classes. Crit. Rev. Biochem. Mol. Biol., 1995, 30, 275-349.
32. Chou, K.C.; Shen, H.B. 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 webservers for predicting subcellular localization of proteins in various organisms. Natural Science, 2010, 2, 1090-1103; doi:10.4236/ns.2010.210136
33. Nat. Protoc., 2008, 3, 153-162.
34. Mohabatkar, H. Prediction of cyclin proteins using Chou's pseudo amino acid composition. Protein Pept. Lett., 2010, 17, 1207-1214.
35. Zhang, S.W.; Zhang, Y.L.; Yang, H.F.; Zhao, C.H.; Pan, Q. 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, 2008, 34, 565-572.
36. Esmaeili, M.; Mohabatkar, H.; Mohsenzadeh, S. Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses. J. Theor. Biol., 2010, 263, 203-209.
37. Sun, X.Y.; Shi, S.P.; Qiu, J.D.; Suo, S.B.; Huang, S.Y.; Liang, R.P. Identifying protein quaternary structural attributes by incorporating physicochemical properties into the general form of Chou's PseAAC via discrete wavelet transform. Mol. Biosyst., 2012, 8, 3178-3184.
38. Ren, L.Y.; Zhang, Y.S.; Gutman, I. Predicting the Classification of Transcription Factors by Incorporating their Binding Site Properties into a Novel Mode of Chou's Pseudo Amino Acid Composition. protein pept. lett., 2012, 19, 1170-1176.
39. Mei, S. Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization. J. Theor. Biol., 2012, 293, 121-130.
40. Mei, S. Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning. J. Theor. Biol., 2012, 310, 80-87.
41. Liao, B.; Xiang, Q.; Li, D. Incorporating Secondary Features into the General form of Chou's PseAAC for Predicting Protein Structural Class. Protein Pept. Lett., 2012, 19, 1133-1138.
42. Cao, J.Z.; Liu, W.Q.; Gu, H. Predicting Viral Protein Subcellular Localization with Chou's Pseudo Amino Acid Composition and Imbalance-Weighted Multi-Label K.-Nearest Neighbor Algorithm. Protein Pept. Lett., 2012, 19, 1163-1169.
43. Chou.K.C.; Shen, H.B. Cell-PLoc: a package of web-servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc., 2008, 3, 153-162.
44. Wang, J.N.; Xu, H.L.; Sun, S.L.; Gao, T.; Li, H.Z.; Li, H.; Su, Z.M. An effective method for accurate prediction of the first hyperpolarizability of alkalides. J. Comput. Chem., 2012, 33(2), 231-236.
45. Wang, J.N; Jin, J.L; Geng, Y; Xu, H.L; Lu, Y.H.; Su, Z.M. An Accurate and Efficient Method to Predict the Electronic Excitation Energies of BODIPY Fluorescent Dyes. J. Comput. Chem., 2012
46. Li, X.; Wang, J.Y.; Zhou, J.P.; Yin, M. A perturb biogeography based optimization with mutation for global numerical optimization. Appl. Math. Comput., 2011, 218(2), 598-609.
47. Li, X.; Yin, M. Multi-operator based Biogeography based Optimization with Mutation for Global Numerical Optimization. Comput. Math. Appl., 2012, 64(9), 2833-2844.
48. Li, X.; Yin, M. An Opposition-Based Differential Evolution Algorithm for Permutation Flow shop Scheduling Based on Diversity Measure. Adv. Eng. Softw., 2013, 55, 10-31.
49. Li, X.; Yin, M. Application of Differential Evolution Algorithm on Self-potential Data. PLOS ONE, 2012, 7(12), e51199. Doi. 10.1371/journal.pone. 0051199.
50. Zhou, J.; Yin, M.; Li, X.; Wang, J. Phase Transitions of EXPSPACE.-Complete Problems: a Further Step. Int. J. Found. Comput. Sci., 2012, 23(1), 173-184.
51. Zhou, J.; Huang, P.; Yin, M.; Zhou, C. Phase Transitions of EXPSPACE.-Complete Problems. Int. J. Found. Comput. Sci., 2010, 21(6), 1073-1088.