Yi Ding

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.

TRAFICA improves TF-DNA binding affinity prediction by integrating open chromatin features and in vitro binding profiles, outperforming existing tools in both in vitro and in vivo settings.

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

Deepurify uses a multi-modal deep language model with contrastive learning to improve MAG decontamination by leveraging genomic sequences and taxonomic lineages.