Jin Xiao

The paper introduces DeepMM, a deep learning method to correct chimeric contigs in MAGs, improving gene annotation accuracy and reducing reference-discordant genes and virulence-factor calls.

DeepMM identifies and corrects metagenomic misassemblies using deep learning, improving downstream binning and increasing near-complete MAGs in a real dataset.

Pangaea improves metagenome assembly using short-reads with barcodes, achieving better contig continuity and more complete genomes than existing assemblers.

LRTK is a platform-agnostic toolkit for linked-read analysis of human genomes and metagenomes, offering simulation, alignment, variant calling, and taxonomic classification.