Lingjie Meng

The paper identifies viral carbohydrate-active genes across diverse viral lineages using a hierarchical orthology framework and reveals their evolutionary and functional diversity.

DeepKOALA is a deep learning framework for KEGG Orthology assignment that improves speed and accuracy over traditional methods and existing tools.

The paper tracks genetic structure and transcription of Heterosigma akashiwo virus during a host bloom, revealing rapid diversification driven by host selection and pre-existing variants.

The paper identifies deep-sea-specific giant viruses with persistent activity and characterizes their unique gene functions adapted to aphotic environments.

The paper identifies and analyzes endogenous dsDNA viral elements across eukaryotic genomes, revealing their distribution and associations with specific host lineages and viral taxa.

This study analyzes giant virus dynamics using metagenomic data, revealing year-round recovery and distinct population dynamics linked to microdiversity and niche breadth.

This study identifies mirusvirus markers in eukaryotic genomes, revealing a broader host range and greater diversity than previously known.

This study uses long-read metagenomics to reconstruct giant virus genomes from a freshwater lake, revealing new species and ecological roles in different water depths.