Yan Fu

PhosSight improves phosphoproteome identification by addressing acquisition biases in DDA and DIA, enhancing sensitivity and reducing missing values in cancer research.

This paper develops VIPA mRNA therapy, which uses viral protease-initiated pyroptosis to suppress viral replication and elicit immune responses in animal models.

DiNovo improves de novo peptide sequencing by using mirror proteases and deep learning, achieving higher coverage and confidence than single-protease methods.

DeepDetect predicts peptide detectability using digestibility features, achieving higher accuracy than existing methods across multiple proteases.

DeepDigest predicts proteolytic cleavage sites for eight proteases using a deep learning model, outperforming traditional methods across multiple datasets.

The paper introduces AP3, an algorithm that improves proteotypic peptide prediction by incorporating peptide digestion probability, achieving higher accuracy than existing tools.

LFAQ improves label-free absolute protein quantification by correcting MS intensity biases using predicted peptide quantitative factors, achieving higher accuracy and precision, especially for low-abundance proteins.