Ian J. Miller

This paper introduces RaPiD-mAb-MS, a direct infusion mass spectrometry method for rapid peptide mapping of monoclonal antibodies, achieving 100-fold faster analysis with high sequence coverage and comparable results to conventional methods.

The paper develops deep learning models to predict FAIMS ion mobility of peptides from sequence, achieving high F2 score on E. coli peptides.

The paper predicts drug classification from chemical structure using CNN and random forests, achieving better accuracy than transcriptomic-based methods.

Autometa improves microbial genome binning in metagenomes by automating clustering and taxonomic partitioning, outperforming existing methods in complex datasets.