ABSTRACT
Based on the chaos game representation, a three-dimensional graphical representation of protein sequence was proposed to describe protein sequence. Then, a numerical characterization methodwas proposed to compare protein sequences. Finally, the nine ND5 proteins are compared based on the numerical characterization to illustrate the method.
- E. Hamori, J. Ruskin (1983). H curves, a novel method of representation of nucleotide series especially suited for long DNA sequences.J BiolChem, 258(2), 1318--1327.Google Scholar
- M.A. Gates (1986). A simple way to look at DNA. J TheorBiol, 119(3), 319--328.Google Scholar
- P.M. Leong, S. Morgenthaler (1995). Random walk and gap plots of DNA sequences. J. Comput. Appl. Biosci, 11, 503--511.Google Scholar
- A. Nandy (1996). A new graphical representation and analysis of DNA sequence structure. I: Methodology and application to globin genes. CurrSci, 70,611--668Google Scholar
- N. Jafarzadeh, A. Iranmanesh (2012). A novel graphical and numerical representation for analyzingDNA sequences based on codons. MATCH, 68, 611--620.Google Scholar
- H.I. Jeffrey (1990). Chaos game representation of gene structure, Nucleic Acids Res, 18, 2163--2170.Google ScholarCross Ref
- P. Wąż, D. Bielińska-Wąż, A. Nandy (2013). Descriptors of 2D-dynamic graphs as a classificationtool of DNA sequences. J Math Chem, 52(1), 132--140.Google ScholarCross Ref
- K. Yamaguchi, S. Mizuta (2014). A new graphical representation of DNA sequences using symmetricalvector assignment. Review of Bioinformatics and Biometrics, 3, 14--21.Google Scholar
- Y. Kobori, S. Mizuta (2016). Similarity estimation between DNA sequences based on local patternhistograms of binary images. Genomics, Proteomics & Bioinformatics. 14(2),103--112.Google ScholarCross Ref
- X. Jin, Q. Jiang, Y.Y. Chen, S.J. Lee, R. Nie, S.W. Yao, D.M. Zhou, K.J. He (2017). Similarity/dissimilarity calculation methods of DNA sequences: A survey. J MolGraph Model, 76, 342--355.Google Scholar
- J.S. Almeida (2014). Sequence analysis by iterated maps, a review. Brief Bioinformitcs, 15(3), 369--375.Google ScholarCross Ref
- J. Ren, X. Bai, Y.Y. Lu, K.J. Tang, Y. Wang, G. Reinert, F.Z. Sun (2018). Alignment-free sequence analysis and applications. Annu Rev Biomed Data Sci, 1, 93--114.Google ScholarCross Ref
- C.T. Zhang, R. Zhang (1991). Analysis of distribution of bases in the coding sequences by a diagrammatic technique, NuclAcids Rev, 19, 6313--6317.Google ScholarCross Ref
- M. Randić, M. Vračko, S.C. Basak (2000). On 3-D graphical representation of DNA primary sequences and their numerical characterization, JChemInfComputSci, 40, 1235--1244.Google Scholar
- N. Jafarzadeh, A. Iranmanesh (2013). C-curve: A novel 3D graphical representation of DNAsequence based on codons. Mathematical Biosciences, 241(2):217--224.Google ScholarCross Ref
- P.Wąż, D. Bielińska-Wąż (2014). 3D-dynamic representation of DNA sequences. JMol Model, 20(3):2141.Google ScholarCross Ref
- M. Randic (2004). 2-D graphical representation of proteins based on virtual genetic code, SAR QSAR Environ Res, 15(3), 147--157.Google ScholarCross Ref
- M. Randic (2007). 2-D graphical representation of proteins based on physicochemical properties of amino acids. ChemPhys Lett, 444(1-3), 176--180.Google Scholar
- P.A. He, X.F. Li, J.L. Yang, J. Wang (2011). A novel descriptor for protein similarity analysis. MATCH Commun Math ComputChem, 65, 445--458.Google Scholar
- Z.H. Qi, M.Z. Jin, S.L. Li, J. Feng (2015). A protein mapping method based on physicochemical properties and dimension reduction. ComputBiol Med, 57, 1--7.Google ScholarDigital Library
- W. Hou, Q. Pan, M. He (2016). A new graphical representation of protein sequences and its applications. Phys A Stat MechAppl, 444(C), 996--1002.Google Scholar
- M. Randic, D. Butina, J. Zupan (2006). Novel 2-D graphical representation of proteins, ChemPhysLett, 419, 528--532.Google Scholar
- P.A. He (2010) A new graphical representationof similarity/dissimilaritystudies of protein sequences.SAR QSAR Environ Res, 21(5-6): 571--580.Google Scholar
- P.A. He, D. Li, Y.P. Zhang, X. Wang, Y.H. Yao (2012). A 3D graphical representation of protein sequences based on the Gray code. J TheorBiol, 304(7), 81--87.Google Scholar
- Y. X. Liu, D. Li, K. B. Lu, Y. D. Jiao, P.A. He (2013). P-H Curve, a Graphical Representation of Protein Sequences for Similarities Analysis, MATCH Commun. Math ComputChem, 70 (1): 451--466.Google Scholar
- T.T. Ma, Y.X. Liu, Q. Dai, Y.H. Yao, P.A. He (2014). A graphical representation of protein sequences based on a novel iterated function system. Phys A Stat MechAppl, 403(1), 21--28.Google ScholarCross Ref
- P.A. He, S.N. Xu, Q. Dai, Y.H. Yao (2016). A generalization of CGR representation for analyzing and comparing protein sequences. Int J Quantum Chem, 116(6), 476--482.Google ScholarCross Ref
- Z. H. Qi, K. C. Li, J. L. Ma, Y. H. Yao, L.Y. Liu (2018) Novel Method of 3-Dimensional GraphicalRepresentation for Proteins and Its Application. Evolutionary Bioinformatics, 14, 1--8.Google ScholarCross Ref
- J. Lin, J. Wei, D. Adjeroh, B.H. Jiang, Y Jiang (2018) SSAW: A new sequence similarity analysis method based on the stationary discrete wavelet transform. BMC Bioinformatics, 19(1),165.Google ScholarCross Ref
- M. M. Abo-Elkhier, M. A. A. Elwahaab, M. A. E. Maaty (2019) Measuring Similarity among Protein Sequences Using aNew Descriptor. Biomed Res Int, 2796971.Google Scholar
- X. F. Cadet, R. Dehak, S. P. Chin, M. Bessafi (2019) Non-Linear Dynamics Analysis of Protein Sequences. Application to CYP450. Entropy, 21, 852.Google ScholarCross Ref
- J. D. Thompson, D. G. Higgins, T. J. Gibson (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res, 22(2), 4673--4680.Google ScholarCross Ref
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- A Graphical Representation of Protein Sequences and Its Applications
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