Chris Soon Heng Tan

sORF-Trans2MS is a two-module deep learning framework that predicts Ribo-supported sORFs and MS-supported microproteins, improving prediction and extending discovery to underrepresented candidates.

The paper uses AI and thermal proteomics to identify a natural product's direct target and shows its therapeutic effect in a psoriasis model.

The paper introduces an automated proteomics sample preparation platform that improves throughput for drug target identification.

This paper introduces PS-SNC, a method for detecting protein complexes from multiple state-specific signed PPI networks, showing improved performance over existing methods.

The paper introduces Slim-TPCA, an optimized method for proteome-wide characterization of protein complex dynamics, showing improved throughput and accuracy in identifying complex dissociation and association under glucose deprivation.