Art F. Y. Poon

The paper analyzes evolutionary patterns of protein-coding genes in RNA viruses, finding no distinction between surface-exposed and non-exposed proteins but significant clustering between enveloped and non-enveloped viruses.

The paper shows that phylogenetic discordance can overestimate reassortment in avian influenza viruses due to reconstruction errors and suggests methods to reduce false positives.

The paper evaluates nine computational tools for identifying SARS-CoV-2 lineages in wastewater sequencing data using simulated samples, finding most tools reliably detect lineages above 5% frequency.

This study uses phylogenetic analysis of influenza A virus sequences to assess if a sequence-based taxonomy can replace serological subtype definitions.

HexSE simulates molecular evolution in overlapping reading frames to assess their impact on selection estimates.

The paper introduces bayroot, a Bayesian method for estimating HIV-1 integration dates using root-to-tip regression, showing improved accuracy over conventional methods.

This paper introduces a method to optimize phylogenetic clustering thresholds for HIV-1 sequence data, showing that optimal thresholds vary by population and improve cluster growth prediction.

The paper introduces community detection methods to improve clustering of infectious disease sequences, demonstrating their application to HIV-1 data to better capture transmission dynamics.

The paper introduces network science-based tree shape statistics for phylogenetic trees, showing they perform as well as or better than traditional measures.

This paper demonstrates how sequencing uncertainty affects phylogenetic lineage assignment and proposes a resampling method to propagate this uncertainty using SARS-CoV-2 data.

The paper introduces CoVizu, a tool for rapidly analyzing and visualizing large SARS-CoV-2 genome datasets, producing consensus trees and beadplot visualizations.

The paper analyzes overlapping reading frames in virus genomes, showing their distribution patterns and developing a graph-based method to visualize and analyze these overlaps.

sierra-local provides a local, secure alternative to web-based HIV-1 drug resistance prediction tools with high concordance and improved performance.

The paper introduces an open-source, alignment-free k-mer based tool for accurate and fast HIV-1 subtype classification, achieving 97% accuracy and outperforming existing methods in speed and privacy.