Hengchuang Yin

scOLAR annotates single-cell RNA-seq data using an ontology-guided framework to detect both known and novel cell types with high accuracy.

KuafuPrimer uses machine learning to design 16S rRNA gene primers with minimal bias, improving taxonomic accuracy and detecting rare taxa missed by universal primers.

This paper introduces VirHRanger, a foundation model for predicting viral host range using genomic and protein data, achieving high accuracy across diverse viruses and host categories.

The paper identifies super compensatory substitutions that restore protein function and confer mutational robustness across diverse genetic backgrounds.

IPEV identifies and classifies prokaryotic and eukaryotic virus-derived sequences in viromes using deep learning, achieving higher precision and efficiency than existing methods.