AccScience Publishing / GPD / Volume 5 / Issue 3 / DOI: 10.36922/GPD026270023
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ORIGINAL RESEARCH ARTICLE

Geometrical study of DNA sequences of New World hantavirus and Nipah virus using the ATG genomic walk method

Guennadi Kouzaev1*
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1 Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering,, Norwegian University of Science and Technology, Trondheim , Norway
GPD 2026, 5(3), 026270023 https://doi.org/10.36922/GPD026270023
Received: 29 June 2026 | Revised: 18 September 2026 | Accepted: 24 September 2026 | Published online: 30 September 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Viral genome analysis is essential for characterizing genetic variation and evolutionary patterns, while complementary computational approaches may provide additional insights beyond conventional sequence-based methods. In this paper, the complete RNAs of New World hantavirus and Nipah virus are analyzed using a DNA walk method that traces the distribution of ATG triplets along sequences. It provides visual one-dimensional models (ATG trajectories) of genomes on a plane and quantitative estimates based on: (i) point-defined relative values of the divergence of ATG trajectories, (ii) relative global-defined standard deviation of ATG triplet numbers in a studied set of sequences, and (iii) relative global-defined standard deviation of fractal dimension values of inter-ATG distances in the same sequence set. These calculated parameters for the two species mentioned are compared with those of previously studied viruses, allowing them to be arranged in the following order based on their increasing sensitivity to variations in ATG distribution: Severe Acute Respiratory Syndrome Coronavirus 2, Middle East Respiratory Syndrome Coronavirus, Nipah, Ebola, and dengue viruses, which is in good accordance with their observed and recognized mutability. The method verified in this paper can be used as a supplementary pre-screening qualitative and quantitative tool for conventional sequencing analysis.

Keywords
ATG genomic walks
Hantavirus
Nipah
Severe Acute Respiratory Syndrome Coronavirus 2
Middle East Respiratory Syndrome Coronavirus
Ebola
Dengue viruses
Funding
None.
Conflict of interest
The author declares no competing interests.
References
  1. The International Committee on Taxonomy of Viruses (ICTV). Accessed on June 12, 2026. https://ictv.global/
  2. Heather JM, Chain B. The sequence of sequencers: The history of sequencing DNA. Genomics. 2016;107(1):1-8. doi: 10.1016/j.ygeno.2015.11.003
  3. The Sequencing Buyer’s Guide 8th Ed. Front Line Genomics. Accessed on April 2, 2026. https://frontlinegenomics.com/sequencing-buyers-guide-8th
  4. GenBank ®. Accessed on June 2, 2026. https://www.ncbi.nlm.nih.gov/genbank/
  5. Global initiative on sharing all influenza data (GISAID). Accessed on June 22, 2026. https://gisaid.org/
  6. NCBI Virus. National Library of Medicine. Accessed on June 22, 2026. https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/
  7. Virus Host DB. https://www.genome.jp/virushostdb/
  8. Bacterial and Viral Bioinformatics Resource Center. Accessed on June 21, 2026. https://www.bv-brc.org/
  9. Lorenzo-Ginori J, Rodriguez-Fuentes A, Abalo R, Rodriguez R. Digital Signal Processing in the Analysis of Genomic Sequences. CBIO. 2009;4(1):28-40. doi: 10.2174/157489309787158134
  10. Ishtyaq Mahmud M, Banerjee T. Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects. Briefings in Bioinformatics. 2026;27(3). doi: 10.1093/bib/bbag229
  11. Nielsen CB, Cantor M, Dubchak I, Gordon D, Wang T. Visualizing genomes: techniques and challenges. Nat Methods. 2010;7(S3):S5-S15. doi: 10.1038/nmeth.1422
  12. Hamori E, Ruskin J. H curves, a novel method of representation of nucleotide series especially suited for long DNA sequences. Journal of Biological Chemistry. 1983;258(2):1318-1327. doi: 10.1016/s0021-9258(18)33196-x
  13. Gates MA. Simpler DNA representation. Nature. 1985;316:219. doi: 10.1038/316219a0
  14. Nandy A, Dey S, Basak SC, Bielińska-Wąż D, Wąż P. Characterization of the Zika virus genome - a bioinformatics study. Curr Comp Aided Drug Design. 2016;12(2):87-97. doi: 10.2174/1573409912666160401115812
  15. Bielińska-Wąż D, Wąż P, Panas D. Applications of 2D and 3D-dynamic representations of DNA/RNA sequences for description of genome sequences of viruses. Comb Chem High Throughput Screen. 2022; 25(3):429-438. doi: 10.2174/1386207324666210804120454
  16. Belinsky A, Kouzaev G. Visual and quantitative analyses of virus genomic sequences using a metric-based algorithm. WSEAS Trans Circ Syst. 2022;21:321-348. doi: 10.37394/23201.2022.21.35
  17. Belinsky A, Kouzaev GA. DNA walks in virus genomics. JP J Biostatistics. 2024;24(2):251-286. doi: 10.17654/0973514324017
  18. The Unicode Consortium. Chapter 2: General Structure. In: The Unicode Standard. 6th ed. The Unicode Consortium; 2010.
  19. Hamming RW. Error-detecting and error-correcting codes. Bell Syst Techn J. 1950;29(2):147–60. doi: 10.1002/j.1538-7305.1950.tb00463.x
  20. Waggener B. Pulse Code Modulation Techniques. Berlin-Heidelberg: Springer-Verlag; 1995.
  21. Navarro G, Raffinot M. Flexible Pattern Matching in Strings: Practical Online Search Algorithms for Texts and Biological Sequences. Cambridge: Cambridge University Press; 2002.
  22. Levenshtein VI. Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady. 1966;10(8):707–710.
  23. Gabidullin E. Theory of codes with maximum rank distance. Probl Inf Trans. 1985;21(1):1-76.
  24. Polityko E. Calculation of distance between strings. MATLAB Central File Exchange. Retrieved March 3, 2021. https://www.mathworks.com/matlabcentral/fileexchange/17585-calculation-of-distance-between-strings
  25. Kyurchiev N, Markov S. Sigmoid functions: Some approximations and modelling aspects. Lambert Acad. Publ; 2015.
  26. Ling Y, He B. Entropic analysis of biological growth models. IEEE Trans. Biomed Eng. 1993;40(12):1193-1200. doi: 10.1109/10.250574
  27. Kouzaev GA. ATG walks in virus genomics. In: Proceeding of the 2nd International Conference Infectious Diseases and Applied Microbiology and Beneficial Microbes, Vienna, Austria, September 25-26, 2025;46. https://www.researchgate.net/publication/396045850_ATG_Walks_in_Virus_Genomics
  28. Cattani C. Fractals and hidden symmetries in DNA. Math Problems Eng. 2010;2010(1). doi: 10.1155/2010/507056
  29. Voss RF. Evolution of long-range fractal correlations and 1/fnoise in DNA base sequences. Phys Rev Lett. 1992;68(25):3805-3808. doi: 10.1103/physrevlett.68.3805
  30. Abramson G, Cerdeira HA, Bruschi C. Fractal properties of DNA walks. Biosystems. 1999;49(1):63-70. doi: 10.1016/s0303-2647(98)00032-x
  31. Hao B, Lee HT, Zhang S. Fractals related to long DNA sequences and complete genomes. Chaos, Solitons and Fractals. 2000;11(6):825-836. doi: 10.1016/S0960-0779(98)00182-9
  32. Su Z-Y, Wu T, Wang S-Y. Local scaling and multifractality spectrum analysis of DNA sequences–GenBank data analysis. Chaos, Solitons and Fractals. 2009;40(4):1750-1765. doi: 10.1016/j.chaos.2007.09.078
  33. Durán-Meza G, López-García J, del Río-Correa JL. The self-similarity properties and multifractal analysis of DNA sequences. Appl Math Nonlin Sci. 2019;4(1):267–278. doi: 10.2478/AMNS.2019.1.00023
  34. Birdi KS. Fractals in Chemistry, Geochemistry, and Biophysics. N.Y.: Plenum Press; 1993.
  35. Dewey TG. Fractals in Molecular Biophysics. Cambridge: Oxford University Press; 1997.
  36. Feder J. Fractals. N.Y.: Plenum Press; 1988.
  37. Grassberger P, Procaccia I. Measuring the strangeness of strange attractors. Physica D. 1983;9(1-2):189-208. doi: 10.1016/0167-2789(83)90298-1
  38. Rasband SN. Chaotic Dynamics of Nonlinear Systems. Weinheim: J. Wiley & Sons; 1989.
  39. Henry B, Lovell N, Camacho F. Nonlinear Dynamics Time Series Analysis. In: Nonlinear Biomedical Signal Processing, Dynamic Analysis and Modeling. IEEE; 2000. doi: 10.1109/9780470545379.ch1
  40. Roueff F, Véhel JL. A regularization approach to fractional dimension estimation. In: Proceedings of Fractals 98. World Scientific; 1998:1-14.
  41. Véhel JL, Legrand P. Signal and image processing with Fraclab, In: Thinking in Patterns. World Scientific; 2004: 321-322. doi: 10.1142/9789812702746_0032
  42. Kouzaev GA. Application of Advanced Electromagnetics. Components and Systems. In: Lecture Notes in Electrical Engineering. Berlin-Heidelberg: Springer; 2013.
  43. Guidolin D, Tortorella C, De Caro R, Agnati LF. Does a self-similarity logic shape the organization of the nervous system? In: Di Leva A, ed. The Fractal Geometry of the Brain. Springer; 2016:137-156. https://link.springer.com/chapter/10.1007/978-1-4939-3995-4_9
  44. Vaidyanathan P, Yoon BJ. The role of signal-processing concepts in genomics and proteomics. J Franklin Inst. 2004;341(1-2):111-135. doi: 10.1016/j.jfranklin.2003.12.001
  45. Karmi A, Najafi A, Gifani P, Khakabimamaghani S. Fractal analysis of DNA by nonlinear genome signal processing for exon and intron separation. Annual Research & Review in Biology. 2014:4(4); 699-708. doi: 10.9734/ARRB/2014/6453
  46. FracLab 2.1. A fractal analysis toolbox for signal and image processing. https://project.inria.fr/fraclab/
  47. Monge-Álvarez J. Weierstrass Cosine Function (WCF). MATLAB Central File Exchange. Retrieved March 21, 2021. https://www.mathworks.com/matlabcentral/fileexchange/50292-weierstrass-cosine-function-wcf
  48. Bradfute SB, Calisher CH, Klempa B, Klingstrom J, Kuhn JH, Laenen L, et al. ICTV Virus Taxonomy Profile: Hantaviridae 2024. J Gen Virology. 2024;105(4):001975. doi: 10.1099/jgv.0.001975
  49. Kuhn JH, Schmaljohn CS. A brief history of Bunyaviral family Hantaviridae. Diseases. 2023;11(1):38. doi: 10.3390/diseases11010038
  50. Zupanc TA, Saksida A, Korva M. Hantavirus infections. Clinical Microbiology and Infection. 2019;21:e6-e16. doi: 10.1111/1469-0691.12291
  51. Muyangwa M, Martynova EV, Khaiboullina SF, Morzunov SP, Rizvanov AA. Hantaviral proteins: structure, functions, and role in Hantavirus infection. Front Microbiol. 2015;6:1326. doi: 10.3389/fmicb.2015.01326
  52. Martínez VP, Di Paola N, Alonso DO, et al. “Super-spreaders” and person-to-person transmission of Andes virus in Argentina. N Engl J Med. 2020;383(23):2230-2241. doi: 10.1056/NEJMoa2009040
  53. Velavan TP, Schmidt-Chanasit J. When rare zoonoses travel: Andes virus, Hantavirus cardiopulmonary syndrome, and the preparedness gap. Int J Infect Disease. 2026;169:108778. doi: 10.1016/j.ijid.2026.108778
  54. Nelson R, Cañate R, Pascale JM, et al. Confirmation of Choclo virus as the cause of hantavirus cardiopulmonary syndrome and high serum antibody prevalence in Panama. J Med Virol. 2010;82(9):1586-1593. doi: 10.1002/jmv.21864
  55. Gonzalez P, Salazar JR, Salinas TP, et al. Two decades of wildlife pathogen surveillance: Case study of Choclo orthohantavirus and its wild reservoir oligoryzomys costaricensis. Viruses. 2023;5(6):1390. doi: 10.3390/v15061390
  56. Albariño CG, Guerrero LW, Chakrabarti AK, Rollin PE, Nichol ST, Newton ILG. Complete genome sequences of Monongahela Hantavirus from Pennsylvania, USA. Microbiol Resour Announc. 2018;7(11):e00928-18. doi: 10.1128/MRA.00928-18
  57. Meier K, Thorkelsson SR, Durieux Trouilleton Q, et al. Structural and functional characterization of the Sin Nombre virus L protein. PLoS Pathog. 2023;19(8):e1011533. doi: 10.1371/journal.ppat.1011533
  58. McMullan LK, Albariño CG, Ksiazek TG, Nichol ST, Spiropoulou CF. Complete genome sequences of a Hantavirus isolate from New York. Genome Announc. 2018;6(12):e00188-18. doi: 10.1128/genomeA.00188-18
  59. Ortega E, Simonson S, Shedroff E, et al. Bayou Hantavirus Cardiopulmonary Syndrome, Louisiana, USA, 2022–2023. Emerg Infect Dis. 2025;31(2):401-403. doi: 10.3201/eid3102.241069
  60. World Health Organization (WHO). Nipah virus fact sheet. Accessed on April 2, 2026. https://www.who.int/news-room/fact-sheets/detail/nipah-virus
  61. Madhukalya R, Yadav U, Parray HA, et al. Nipah virus: pathogenesis, genome, diagnosis, and treatment. Appl Microbiol Biotechnol. 2025;109(1):158. doi: 10.1007/s00253-025-13474-6
  62. Asokan S, Luke MS, Atiyah HM, et al. Nipah virus as a pandemic threat: Current knowledge, diagnostic gaps, and future research priorities. Diagnostic Microbiology and Infectious Disease. 2026;114(2):117141. doi: 10.1016/j.diagmicrobio.2025.117141
  63. Branda F, Ceccarelli G, Giovanetti M, et al. Nipah Virus: A Zoonotic Threat Re-Emerging in the Wake of Global Public Health Challenges. Microorganisms. 2025;13(1):124. doi: 10.3390/microorganisms13010124
  64. Tan FH, Sukri A, Idris N, et al. A systematic review on Nipah virus: global molecular epidemiology and medical countermeasures development. Virus Evolution. 2024;10(1). doi: 10.1093/ve/veae048
  65. Whitmer SLM, Lo MK, Sazzad HMS, et al. Inference of Nipah virus evolution, 1999–2015. Virus Evolution. 2020;7(1). doi: 10.1093/ve/veaa062
  66. Rahman MdM, Miah M, Hossain ME, et al. Development of a culture-independent whole-genome sequencing of Nipah virus using the MinION Oxford Nanopore platform. Microbiol Spectr. 2025;13(6). doi: 10.1128/spectrum.02492-24
  67. Cortes-Azuero O, Lefrancq N, Nikolay B, et al. The genetic diversity of Nipah virus across spatial scales. J Infect Dis. 2024;230(6):e1235-e1244. doi: 10.1093/infdis/jiae221
  68. Hauser N, Gushiken AC, Narayanan S, Kottilil S, Chua JV. Evolution of Nipah Virus Infection: Past, Present, and Future Considerations. TropicalMed. 2021;6(1):24. doi: 10.3390/tropicalmed6010024
  69. Sudeep AB, Yadav PD, Gokhale MD, et al. Detection of Nipah virus in Pteropus medius in 2019 outbreak from Ernakulam district, Kerala, India. BMC Infect Dis. 2021;21(1). doi: 10.1186/s12879-021-05865-7
  70. Lv C, He J, Zhang Q, Wang T. Vaccines and Animal Models of Nipah Virus: Current Situation and Future Prospects. Vaccines. 2025;13(6):608. doi: 10.3390/vaccines13060608
  71. Faus-Cotino J, Reina G, Pueyo J. Nipah Virus: A Multidimensional Update. Viruses. 2024;16(2):179. doi: 10.3390/v16020179
  72. Turki TG, Ghayyib AA. Mechanisms leading to the loss of the AUG codon function as a translation initiator: A review. Gene Protein Dis. 2026. doi: 10.36922/GPD025350065
  73. Ma X, Shao Y, Tian L, et al. Analysis of error profiles in deep next-generation sequencing data. Genome Biol. 2019;20(1):50. doi: 10.1186/s13059-019-1659-6
  74. Stoler N, Nekrutenko A. Sequencing error profiles of Illumina sequencing instruments. NAR Genome Bioinform. 2021;3(1):1-9. doi: 10.1093/nargab/lqab019
  75. Dempsey R, Goldswain H, Newman J, et al. Characterisation of Naturally Occurring MERS-CoV Spike Mutations and Their Impact on Fusion and Neutralisation. Viruses. 2026;18(3):377. doi: 10.3390/v18030377
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