A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models.
Journal:
Scientific data
Published Date:
Nov 8, 2024
Abstract
Training machine learning models for tasks such as de novo sequencing or spectral clustering requires large collections of confidently identified spectra. Here we describe a dataset of 2.8 million high-confidence peptide-spectrum matches derived from nine different species. The dataset is based on a previously described benchmark but has been re-processed to ensure consistent data quality and enforce separation of training and test peptides.