Yuguo Zha

This paper introduces ONN4MST, a deep learning method for microbial source tracking that achieves high accuracy and speed across large datasets of microbial communities.

This paper introduces ONN4ARG, an ontology-aware deep learning method for antibiotic resistance gene discovery, identifying 120,726 candidate ARGs, including novel ones not in public databases.

GAN-GMHI improves disease prediction by enhancing the discrimination power of a gut microbiome-based health index through batch effect removal using a generative adversarial network.

The paper introduces ContactLib-ATT, a two-level neural network for protein structure embedding that improves SCOP superfamily classification and remote homolog search.

EXPERT uses transfer learning to improve microbial source tracking, showing better efficiency and accuracy in tracking gut microbiome changes in infants and colorectal cancer patients.