Jimmy K. Eng

The paper develops a deep learning-enhanced fragment ion indexing method to reduce memory usage in tandem mass spectrometry searches while maintaining search accuracy and speed.

The paper constructs a spatiotemporal atlas of the androgen receptor proximal interactome using PL-qMS, identifying 4,751 AR-PIPs and revealing a retromer-AR-TMF1 axis involved in androgen-regulated transcription.

The paper introduces SYNTAX, a method to analyze sequence motifs in the androgen receptor interactome, revealing key motifs and their organization across different compartments and time points.

The paper identifies two modes of nuclear receptor engagement through LXXLL motifs, showing how AR-V7 loses LXXLL-enriched interactions in cancer.

This paper enhances the Comet search engine with fragment-ion indexing, improving peptide spectral matching speeds by up to 94% while maintaining accuracy in proteomics applications.

The paper summarizes recent developments in the Crux toolkit for analyzing bottom-up proteomics data, including speedups, new features, and tools.

The paper introduces a method to coisolate and fragment SILAC peptide pairs for improved identification and quantification in MS/MS-based proteomics.

The paper introduces PEFF, a new format for proteomics data that enhances FASTA with metadata for sequence variants and PTMs, enabling better analysis in proteogenomics and top-down proteomics.