Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species

Year : 2026 | Volume : 04 | Issue : 01 | Page : 33 45
    By

    Sathi Lakshmi Teja Sri,

  • Manas Kumar Yogi,

  1. Undergraduate Student, Department of Computer Science and Engineering, Pragati Engineering College, Surampalem, Andhra Pradesh, India
  2. Assistant Professor, Department of Computer Science and Engineering, Pragati Engineering College, Surampalem, Andhra Pradesh, India

Abstract

The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems. Traditional phylogenetic methods are accurate but become more expensive when they are processing with thousands of marine taxa parallelly. This article shows a critical analysis of parallel greedy algorithms as an adaptable solution for large-scale marine phylogenetics. It examines the main principles of greedy heuristics applied in the construction of tree based on distance, specifically on neighbor joining and its variations. The paper demonstrates that the implementation of the parallelization techniques, data parallelism, task parallelism, and the hybrid models may be utilized to overcome the time complexity factors that restrict the use of the traditional implementation of the usual methods in a quadratic manner. The analysis integrates current advances in shared computing architectures, graphical processing units (GPU) acceleration, and algorithmic optimizations that show the working of marine metagenomic datasets that have tens of thousands of operational taxonomic units. Performance improvements are evaluated in various fields of marine research, such as microbial community studies and vertebrate evolutionary studies, and examples of nearly linear speedup of parallel greedy approaches on high-performance computing clusters have been documented. In addition to this, we discuss the synthesis of these methods with advanced technologies such as cloud computing and software containerization to enable accessible marine biodiversity studies. The results show that parallel greedy methods decrease phylogenetic rebuilding time complexity from days to hours for datasets containing 10,000+ marine species, showcasing live analysis of natural samples and providing large-scale evolutionary studies crucial for conservation and climate impact assessment.

Keywords: High-performance computing (HPC), marine genomics, metagenomic datasets, parallel greedy algorithms, phylogenetic tree reconstruction, Scalable phylogenetic pipelines

[This article belongs to International Journal of Algorithms Design and Analysis Review ]

How to cite this article:
Sathi Lakshmi Teja Sri, Manas Kumar Yogi. Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species. International Journal of Algorithms Design and Analysis Review. 2026; 04(01):33-45.
How to cite this URL:
Sathi Lakshmi Teja Sri, Manas Kumar Yogi. Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species. International Journal of Algorithms Design and Analysis Review. 2026; 04(01):33-45. Available from: https://journals.stmjournals.com/ijadar/article=2026/view=241166


References

  1. Stewart EEM, Hartmann FT, Morgenstern Y, Storrs KR, Maiello G, Fleming RW. Mental object rotation based on two-dimensional visual representations. Curr Biol. 2022;32(21):R1224–R1225. doi:10.1016/j.cub.2022.09.036. PMID: 36347228.
  2. Lin X, Amalraj M, Blanton C, Avila B, Holmes TC, Nitz DA, Xu X. Noncanonical projections to the hippocampal CA3 regulate spatial learning and memory by modulating the feedforward hippocampal trisynaptic pathway. PLoS Biol. 2021;19(12):e3001127. doi:10.1371/journal.pbio.3001127. PMID: 34928938.
  3. Kapli P, Yang Z, Telford MJ. Phylogenetic tree building in the genomic age. Nat Rev Genet. 2020;21(7):428–444. doi:10.1038/s41576-020-0233-0. PMID: 32424311.
  4. Purkayastha P, Pendyala K, Saxena AS, Hakimjavadi H, Chamala S, Dixit P, Baer CF, Lele TP. Reverse plasticity underlies rapid evolution by clonal selection within populations of fibroblasts propagated on a novel soft substrate. Mol Biol Evol. 2021;38(8):3279–3293. doi:10.1093/molbev/msab102. PMID: 33871606.
  5. Borenstein E, Kupiec M, Feldman MW, Ruppin E. Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proc Natl Acad Sci U S A. 2008;105(38):14482–14487. doi:10.1073/pnas.0806162105. PMID: 18787117.
  6. Sunagawa S, Acinas SG, Bork P, Bowler C, Tara Oceans Coordinators, Eveillard D, Gorsky G, Guidi L, Iudicone D, Karsenti E, Lombard F, et al. Tara Oceans: Towards global ocean ecosystems biology. Nat Rev Microbiol. 2020;18(8):428–445. doi:10.1038/s41579-020-0364-5. PMID: 32398798.
  7. Obradovic A, Chowdhury N, Haake SM, Ager C, Wang V, Vlahos L, Guo XV, Aggen DH, Rathmell WK, Jonasch E, Johnson JE, et al. Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages. Cell. 2021;184(11):2988–3005.e16. doi:10.1016/j.cell.2021.04.038. PMID: 34019793.
  8. Karmin M, Flores R, Saag L, Hudjashov G, Brucato N, Crenna-Darusallam C, Larena M, Endicott PL, Jakobsson M, Lansing JS, Sudoyo H, et al. Episodes of diversification and isolation in Island Southeast Asian and Near Oceanian male lineages. Mol Biol Evol. 2022;39(3):msac045. doi:10.1093/molbev/msac045. PMID: 35294555.
  9. Ren Y, Chakraborty T, Doijad S, Falgenhauer L, Falgenhauer J, Goesmann A, Hauschild AC, Schwengers O, Heider D. Prediction of antimicrobial resistance based on whole-genome sequencing and machine learning. Bioinformatics. 2022;38(2):325–334. doi:10.1093/bioinformatics/btab681. PMID: 34613360.
  10. Price MN, Dehal PS, Arkin AP. FastTree 2: Approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5:e9490. doi:10.1371/journal.pone.0009490. PMID: 20224823.
  11. Friedman ST, Collyer ML, Price SA, Wainwright PC. Divergent processes drive parallel evolution in marine and freshwater fishes. Syst Biol. 2022;71(6):1319–1330. doi:10.1093/sysbio/syab080. PMID: 34605882.
  12. Nyström-Persson J, Keeble-Gagnère G, Zawad N. Compact and evenly distributed k-mer binning for genomic sequences. Bioinformatics. 2021;37(17):2563–2569. doi:10.1093/bioinformatics/btab156. PMID: 33693556.
  13. Gao Y, Liu Y, Ma Y, Liu B, Wang Y, Xing Y. abPOA: An SIMD-based C library for fast partial order alignment using adaptive band. Bioinformatics. 2021;37(15):2209–2211. doi:10.1093/bioinformatics/btaa963. PMID: 33165528.
  14. Hughes EC, Edwards DP, Thomas GH. The homogenization of avian morphological and phylogenetic diversity under the global extinction crisis. Curr Biol. 2022;32(17):3830–3837.e3. doi:10.1016/j.cub.2022.06.018. PMID: 35868322.
  15. Shao H, Ruan J. BSAlign: a library for nucleotide sequence alignment. Genomics Proteomics Bioinformatics. 2024;22(2):qzae025. doi:10.1093/gpbjnl/qzae025. PubMed:39209796.
  16. Czech L, Stamatakis A. Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples. PLoS One. 2019;14(5):e0217050. doi:10.1371/journal.pone.0217050. PMID: 31136592.
  17. Günder M, Ispizua Yamati FR, Kierdorf J, Roscher R, Mahlein AK, Bauckhage C. Agricultural plant cataloging and establishment of a data framework from UAV-based crop images by computer vision. Gigascience. 2022;11:giac054. doi:10.1093/gigascience/giac054. PMID: 35715875.
  18. Yap TK, Frieder O, Martino RL. Parallel computation in biological sequence analysis. IEEE Trans Parallel Distrib Syst. 1998;9(3):283–294. doi:10.1109/71.674320.
  19. van Rosmalen L, Riedstra B, Beemster N, Dijkstra C, Hut RA. Differential temperature effects on photoperiodism in female voles: A possible explanation for declines in vole populations. Mol Ecol. 2022;31(12):3360–3373. doi:10.1111/mec.16467. PMID: 35398940.
  20. Johnston A, Matechou E, Dennis EB. Outstanding challenges and future directions for biodiversity monitoring using citizen science data. Methods Ecol Evol. 2023;14:103–116. doi:10.1111/2041-210X.13834.

Regular Issue Subscription Review Article
Volume 04
Issue 01
Received 09/03/2026
Accepted 18/03/2026
Published 28/04/2026
Publication Time 50 Days


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