Abstract
Phylogenetics is a fundamental component of evolutionary analysis frameworks in biology (Yang, 2014) and linguistics (Atkinson & Gray, 2005).Recently, the advent of large-scale genomics and the SARS-CoV-2 pandemic has highlighted the necessity for phylogenetic software to handle large datasets (Attwood et al., 2022;Kapli et al., 2020;Khurana et al., 2024;Kraemer et al., 2025).While significant efforts have focused on scaling optimisation algorithms (De Maio et al., 2023;Sanderson, 2021;Turakhia et al., 2021), visualisation (Sanderson, 2022), and lineage identification (McBroome et al., 2024), an emerging body of research has been dedicated to efficient representations of data for genomes (Deorowicz et al., 2023) and phylogenetic trees (Chauve et al., 2025;Penn et al., 2025;Richman et al., 2025).Compared to the traditional Newick format which represents trees using strings of nested parentheses (Felsenstein, 2004), modern tree representations utilise integer vectors to define the tree topology traversal.This approach offers several advantages, including easier manipulation, increased memory efficiency, and applicability to machine learning.
Samir Bhatt
Professor, FMedSci, MAE; Scientific Director of GPAP
Statistics, machine learning and Bayesian inference for public health and infectious diseases.