Phylogenetic analysis of DNA sequences based on k-word and rough set theory

Physica A: Statistical Mechanics and its Applications

Volumn 398, Issue , 2014, Pages 162-171

  Li, Chun ^a,b   Yang, Yan ^a   Jia, Meiduo ^a   Zhang, Yingying ^a   Yu, Xiaoqing ^c   Wang, Changzhong ^a  

^a BOHAI UNIVERSITY   (China)

^b Processing and Safety Control of Liaoning Province   (China)

^c SHANGHAI INSTITUTE OF TECHNOLOGY   (China)

Author keywords

DNA; Feature selection; k word; Phylogenetic analysis; Rough set theory

Indexed keywords

DNA; DNA SEQUENCES; FEATURE EXTRACTION; LINGUISTICS;

ALIGNMENT-FREE; CHARACTERISTIC SEQUENCE; MOLECULAR PHYLOGENETIC ANALYSIS; PHYLOGENETIC ANALYSIS; ROUGH SET THEORY (RST); SEQUENCE COMPARISONS; TRAINING SETS; WORD FREQUENCIES;

ROUGH SET THEORY;

EID: 84891791887     PISSN: 03784371     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.physa.2013.12.025     Document Type: Article

References (55)

1. H.H. Otu, and K. Sayood A new sequence distance measure for phylogenetic tree construction Bioinformatics 19 2003 2122 2130 (Pubitemid 37408164)
2. H.J. Jeffrey Chaos game representation of gene structure Nucleic Acids Res. 18 1990 2163 2170
3. A. Nandy Graphical representation of long DNA sequences Curr. Sci. 66 1994 821
4. A. Nandy, and S.C. Basak New approaches to drug-DNA interactions based on graphical representation and numerical characterization of DNA sequences Curr. Comput. Aided Drug Des. 6 2010 283 289
5. A. Ghosh, and A. Nandy Graphical representation and mathematical characterization of protein sequences and applications to viral proteins Adv. Protein Chem. Struct. Biol. 83 2011 1 42
6. R. Zhang, and C.T. Zhang Z curves, an intuitive tool for visualizing and analyzing DNA sequences J. Biomol. Struct. Dyn. 11 1994 767 782 (Pubitemid 24089977)
7. C.T. Zhang, and J. Wang Recognition of protein coding genes in the yeast genome at better than 95% accuracy based on the Z curve Nucleic Acids Res. 28 2000 2804 2814 (Pubitemid 30488023)
8. M. Randić, M. Vračko, A. Nandy, and S.C. Basak On 3-D graphical representation of DNA primary sequence and their numerical characterization J. Chem. Inf. Comput. Sci. 40 2000 1235 1244
9. M. Randić, M. Vračko, N. Lerš, and D. Plavsić Novel 2-D graphical representation of DNA sequences and their numerical characterization Chem. Phys. Lett. 368 2003 1 6 (Pubitemid 36002823)
10. M. Randić, and A.T. Balaban On a four-dimensional representation of DNA primary sequences J. Chem. Inf. Comput. Sci 43 2003 532 539
11. M. Randić, M. Novic, and D. Plavsić Milestones in graphical bioinformatics Int. J. Quantum Chem. 113 2013 2413 2446
12. M. Randić, J. Zupan, A.T. Balaban, D. Vikic-Topic, and D. Plavsić Graphical representation of proteins Chem. Rev. 111 2011 790 862
13. S.T. Yau, J.S. Wang, A. Niknejad, C.X. Lu, N. Jin, and Y.K. Ho DNA sequence representation without degeneracy Nucleic Acids Res. 31 2003 3078 3080 (Pubitemid 37441767)
14. M. Deng, C.L. Yu, Q. Liang, R.L. He, and S.T. Yau A novel method of characterizing genetic sequences: genome space with biological distance and applications PLoS One 6 3 2011 e17293
15. Y.S. Zhang, and M.S. Tan Visualization of DNA sequences based on 3DD-curves J. Math. Chem. 44 2008 206 216
16. Z.J. Zhang DV-curve: a novel intuitive tool for visualizing and analyzing DNA sequences Bioinformatics 25 2009 1112 1117
17. B. Liao, B.Y. Liao, X.G. Lu, and Z. Cao A novel graphical representation of protein sequences and its application J. Comput. Chem. 32 2011 2539 2544
18. G.S. Xie, and Z.X. Mo Three 3D graphical representations of DNA primary sequences based on the classifications of DNA based and their applications J. Theoret. Biol. 269 2011 123 130
19. C. Li, N. Tang, and J. Wang Directed graphs of DNA sequences and their numerical characterization J. Theoret. Biol. 241 2006 173 177 (Pubitemid 43993954)
20. C. Li, X.Q. Yu, L. Yang, X.Q. Zheng, and Z.F. Wang 3-D maps and coupling numbers for protein sequences Physica A 388 2009 1967 1972
21. Z.H. Qi, L. Li, and X.Q. Qi Using Huffman coding method to visualize and analyze DNA sequences J. Comput. Chem. 32 2011 3233 3240
22. M. Randic, M. Novic, M. Vracko, and D. Plavsic Study of proteome maps using partial ordering J. Theoret. Biol. 266 2010 21 28
23. M. Randic Very efficient search for nucleotide alignments J. Comput. Chem. 34 2013 77 82
24. P.A. He, and J. Wang Characteristic sequences for DNA primary sequence J. Chem. Inf. Comput. Sci. 42 2002 1008 1085
25. A. Lempel, and J. Ziv On the complexity of finite sequences IEEE Trans. Inform. Theory 22 1976 75 81
26. M. Burrows, and D.J. Wheeler A Block-Sorting Lossless Data Compression Algorithm, SRC Research Report, 124 1994
27. S. Mantaci, A. Restivo, and M. Sciortino Burrows-Wheeler transform and Sturmian words Inform. Process. Lett. 86 2003 241 246
28. S. Mantaci, A. Restivo, G. Rosone, and M. Sciortino An extension of the Burrows-Wheeler transform Theoret. Comput. Sci. 387 2007 298 312 (Pubitemid 47633446)
29. S. Mantaci, A. Restivo, and M. Sciortino Distance measures for biological sequences: some recent approaches Int. J. Approx. Reason. 47 2008 109 124 (Pubitemid 350138355)
30. S. Mantaci, A. Restivo, G. Rosone, and M. Sciortino A new combinatorial approach to sequence comparison Theory Comput. Syst. 42 2008 411 429
31. C. Li, Z.X. Li, X.Q. Zheng, H. Ma, and X.Q. Yu A generalization of Lempel-Ziv complexity and its application to the comparison of protein sequences J. Math. Chem. 48 2010 330 338
32. X. Zheng, C. Li, and J. Wang A complexity-based measure and its application to phylogenetic analysis J. Math. Chem. 46 2009 1149 1157
33. X. Zheng, C. Li, and J. Wang An information-theoretic approach to the prediction of protein structural class J. Comput. Chem. 31 2010 1201 1206
34. Y. Zhang, J.K. Hao, C.J. Zhou, and K. Chang Normalized Lempel-Ziv complexity and its application in bio-sequence analysis J. Math. Chem. 46 2009 1203 1212
35. L.P. Yang, G.S. Chang, and X.D. Zhang Use of the Burrows-Wheeler similarity distribution to the comparison of the proteins Amino Acids 39 2010 887 898
36. S. Karlin, and C. Burge Dinucleotide relative abundance extremes: a genomic signature Trends Genet. 11 1995 283 290
37. B.L. Hao, J. Qi, and B. Wang Prokaryotic phylogeny based on complete genomes without sequence aligment Modern Phys. Lett. B 17 2003 1 4
38. J. Qi, B. Wang, and B.L. Hao Whole proteome prokaryote phylogeny without sequence alignment: a k-string composition approach J. Mol. Biol. 58 2004 1 11 (Pubitemid 38120400)
39. L. Gao, J. Qi, J.D. Sun, and B.L. Hao Prokaryote phylogeny meets taxonomy: an exhaustive comparison of composition vector trees with systematic bacteriology Sci. China C. Life Sci. 50 2007 587 599 (Pubitemid 47459905)
40. H. Wang, Z. Xu, L. Gao, and B.L. Hao A fungal phylogeny based on 82 complete genomes using the composition vector method BMC Evol. Biol. 195 2009 1 13
41. Q. Dai, and T. Wang Comparison study on k-word statistical measures for protein: from sequence to 'sequence space' BMC Bioinformatics 9 2008 394
42. Q. Dai, X.Q. Liu, Y.H. Yao, and F. Zhao Numerical characteristics of word frequencies and their application to dissimilarity measure for sequence comparison J. Theoret. Biol. 276 2011 174 180
43. X.M. Wu, Z. Cai, X.F. Wan, T. Hoang, R. Goebel, and G.H. Lin Nucleotide composition string selection in HIV-1 subtyping using whole genomes Bioinformatics 23 2007 1744 1752 (Pubitemid 47250306)
44. Y. Zhang, X. Wang, and L. Kang A k-mer scheme to predict piRNAs and characterize locust piRNAs Bioinformatics 27 2011 771 776
45. X.W. Yang, and T.M. Wang A novel statistical measure for sequence comparison on the basis of k-word counts J. Theoret. Biol. 2 2013 91 100
46. X.Q. Yu, X.Q. Zheng, L.Y. Meng, C. Li, and J. Wang A support vector machines based method to predict success for polymerase chain reactions Comb. Chem. High Throughput Screen 15 2012 486 491
47. Z. Liu, J. Meng, and X. Sun A novel feature-based method for whole genome phylogenetic analysis without alignment: application to HEV genotyping and subtyping Biochem. Biophys. Res. Commun. 368 2008 223 230
48. S.Y. Ding, Q. Dai, H.M. Liu, and T.M. Wang A simple feature representation vector for phylogenetic analysis of DNA sequences J. Theoret. Biol. 265 2010 618 623
49. Y.J. Huang, L.P. Yang, and T.M. Wang Phylogenetic analysis of DNA sequences based on the generalized pseudo-amino acid composition J. Theoret. Biol. 269 2011 217 223
50. B. Walczak, and D.L. Massart Tutorial rough sets theory Chemometr. Intell. Lab. Syst. 47 1999 1 16
51. Q.H. Hu, H. Zhao, Z.X. Xie, and D.R. Yu Consistency based attribute reduction PAKDD Lecture Notes in Computer Science vol. 4426 2007 96 107
52. C.Z. Wang, W. Du, On covering rough set based attribute reduction, in: 2010 Second WRI Global Congress on Intelligent Systems, Vol. 2, 2010, pp. 96-99.
53. C.Z. Wang, D.G. Chen, and Q.H. Hu Some invariant properties of ordered information systems under homomorphism Sci. China Inf. Sci. 53 2010 1816 1825
54. P.P. Yao, H.P. Zhu, X.Z. Deng, F. Xu, R.H. Xie, C.H. Yao, J.Q. Weng, Y. Zhang, Z.Q. Yang, and Z.Y. Zhu Molecular evolution analysis of hantaviruses in Zhejiang province Chin. J. Virol. 26 2010 465 470
55. L. Lu, C. Li, and C.H. Hagedorn Phylogenetic analysis of global hepatitis E virus sequences: genetic diversity, subtypes and zoonosis Rev. Med. Virol. 16 2006 5 36 (Pubitemid 43133591)