Eugenia Voytik

AlphaPept is an open-source framework for efficient processing of large MS-based proteomics datasets, achieving significant speed improvements using Python and machine learning.

AlphaPeptDeep predicts peptide properties using deep learning, offering a modular framework that matches or exceeds existing tools for retention time, ion mobility, and fragment intensity prediction.

AlphaViz validates proteomics results by visualizing raw data and comparing with automated analysis outputs.

AlphaMap visually annotates proteomics data with sequence-specific knowledge, enabling integration of experimental results with UniProt annotations and proteolytic cleavage sites.

The paper measures CCS values for a million peptides across five organisms and develops a method to predict CCS for any peptide and organism.

AlphaTims enables fast access and visualization of high-dimensional LC-TIMS-QTOF proteomics data through efficient indexing and just-in-time compilation.

The paper introduces a new DIA scan mode that improves peptide precursor ion sampling and identification specificity using ion mobility, achieving high proteome coverage and accuracy.