Yuxuan Pang

PharaCon uses a conditional BERT framework to improve phage identification in metagenomic data by incorporating label constraints during pre-training.

This paper introduces STForte, a method for spatially resolved transcriptomics analysis that matches expression profiles with spatial topology, improving downstream analysis and spatial enhancement.

KBPRNA predicts kinase activity from bulk RNA-seq data using machine learning, outperforming existing methods in cancer tissue samples.

This study uses mass spectrometry and machine learning to predict antibiotic susceptibility of Staphylococcus aureus, enabling faster and more accurate treatment decisions.