Uri Keich

The paper introduces an FDR control procedure for de novo peptide sequencing and demonstrates its validity and utility.

The paper introduces PIP-ECHO, a method to control false discovery rate in peptide-identity-propagation, showing it outperforms existing tools in FDR control and differential protein abundance detection.

This paper evaluates FDR control in mass spectrometry proteomics tools, finding that none consistently control FDR at the peptide level in DIA data, especially for single-cell datasets.

The paper introduces Percolator-RESET, a post-processor for tandem mass spectrometry proteomics that better controls the false discovery rate than Percolator.

The paper evaluates blastp's E-value and proposes an alternative significance analysis that provides more accurate alignment scores.

The paper investigates FDR control in proteomics MS/MS database searches, finding no strong evidence of issues in open modification or narrow window approaches after accounting for chimeric spectra and candidate differences.

The paper introduces CONGA, a method that combines narrow and open modification searches to improve detection of post-translational modifications while maintaining statistical power.

Crema is an open-source Python tool that implements target-decoy competition methods for estimating false discovery rates in proteomics experiments.

The paper improves peptide-level mass spectrometry analysis by showing that double competition (PSM-and-peptide) outperforms single competition (PSM-only) in discovering peptides at a 1% FDR threshold.

Group-walk improves FDR control in grouped data by incorporating group structure, achieving power gains in peptide discovery across different groups.

This paper introduces a workflow to build spectral libraries from DIA mass spectrometry data, showing it can detect phosphorylated peptides and outperforms library-free methods in accuracy and sensitivity.

The paper introduces a new method to control the false discovery rate in proteomics when only a subset of peptides are relevant, showing it outperforms existing methods.

The paper introduces an averaging strategy to reduce variability in FDR estimates from target-decoy competition in shotgun proteomics.