Nhan Ly-Trong

The paper develops PhyCD to detect contamination in SARS-CoV-2 genomes, identifying 10,942 putative contamination events across nearly 5 million genomes.

ProtFinder is a machine learning framework for protein model selection that outperforms existing methods in accuracy and speed on real datasets.

This paper introduces a site-specific mutation model (SSM) for pandemic-scale phylogenetics, showing it better captures mutation patterns in SARS-CoV-2 genomes than classical models.

The paper investigates whether tryptophan was present in LUCA by analyzing the evolution of tryptophanyl-tRNA synthetase and finds that W usage originated in Bacteria with later horizontal transfer to Archaea.

GTRspmix improves protein phylogenetics by incorporating multiple exchangeability matrices into mixture models, enhancing fit and reducing long-branch attraction artifacts.

CMAPLE 2 improves phylogenetic inference speed and memory efficiency for large pathogen genome datasets, enabling analysis of nearly four million SARS-CoV-2 genomes in 12 days.

The paper improves pandemic-scale phylogenetic analysis by addressing mutation rate variation and sequence errors, reconstructing a reliable phylogenetic tree of over 2 million SARS-CoV-2 genomes.

TreeFormer improves phylogenetic tree reconstruction accuracy using a transformer-based tree rearrangement method, outperforming FastTree 2 on small alignments.

SPRTA assesses phylogenetic confidence by evaluating evolutionary histories rather than clades, applied to a global SARS-CoV-2 dataset.

The paper introduces CMAPLE, an optimized phylogenetic inference method, and integrates it into IQ-TREE 2 for improved pandemic-scale genomic analysis.

AliSim efficiently simulates biologically realistic alignments under complex evolutionary models, outperforming existing tools in speed and resource usage.