Song Feng

ProteoMeter integrates multi-PTM and limited proteolysis data to map proteomic changes to residue level, demonstrating its use in analyzing HCoV-229E infection.

The paper integrates AMGs and phage assembly into a genome-scale metabolic model to predict their impact on host metabolism and phage production, revealing synergistic and antagonistic effects.

The paper introduces CLEAN-Contact, a contrastive learning framework for enzyme function prediction using amino acid sequences and contact maps, showing improved accuracy over existing methods.

The paper investigates how biochemical reaction networks perform signal integration and integral feedback control, finding that these capabilities overlap but are not always mutually exclusive.

The paper generates a deep phosphoproteomics dataset of the EGFR-MAPK pathway in MCF10A cells and integrates it with protein databases to study kinase signaling.

This paper introduces TIFF, a method enhancing single-cell proteomics sensitivity and accuracy by filtering background ions and using 3D MS1 feature matching, achieving deep proteome analysis in single cells.

This paper introduces a nested nanowell chip to improve single-cell proteomics throughput and robustness, demonstrating the ability to quantify ~1500 proteins from ~100 cells with low abundance variation.

BayesDeBulk estimates immune and stromal cell composition from bulk proteomic and transcriptomic data, outperforming existing tools in synthetic and real data examples.

The paper identifies a thiamine auxotrophy in Serendipita indica and shows that co-culturing with Bacillus subtilis restores growth, but only under specific spatial and temporal conditions.