Canh Hao Nguyen

Improving Biological Sequence Prediction with AlphaFold2 Representation

The paper evaluates AlphaFold2's representation for improving sequence-based prediction tasks, showing superior performance over traditional features.

DeepKOALA: A Fast and Accurate Deep Learning Framework for KEGG Orthology Assignment

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

Efficient inference of large pangenomes with PanTA

PanTA efficiently constructs large bacterial pangenomes, outperforming existing tools in speed while maintaining accuracy and enabling progressive updates without rebuilding from scratch.

AMRomics: a scalable workflow to analyze large microbial genome collection

AMRomics is a scalable pipeline for analyzing large microbial genome collections, showing better performance than existing tools.

Pasa: Leverage population pangenome graph to scaffold prokaryote genome assemblies.

Pasa improves genome scaffolding by using population pangenome graphs, enhancing accuracy and efficiency for bacterial genome assemblies.

XGSEA: CROSS-species Gene Set Enrichment Analysis via domain adaptation

XGSEA predicts gene set enrichment significance in one species using gene expression from another species through domain adaptation and regression.