biostudies-literatureUnknown16(1)Liu ZData-independent acquisition mass spectrometry (DIA-MS) has become increasingly pivotal in quantitative proteomics. In this study, we present DIA-BERT, a software tool that harnesses a transformer-based pre-trained artificial intelligence (AI) model for analyzing DIA proteomics data. The identification model was trained using over 276 million high-quality peptide precursors extracted from existing DIA-MS files, while the quantification model was trained on 34 million peptide precursors from synthetic DIA-MS files. When compared to DIA-NN, DIA-BERT demonstrated a 51% increase in protein identifications and 22% more peptide precursors on average across five human cancer sample sets (cervical cancer, pancreatic adenocarcinoma, myosarcoma, gallbladder cancer, and gastric carcinoma), achieving Nature communications3530https://www.ebi.ac.uk/biostudies/studies/S-EPMC11997033biostudies-literatureDIA-BERT: pre-trained end-to-end transformer models for enhanced DIA proteomics data analysis.PMC11997033Liu ZZhang YZhang XLiu PNie ZChen YGuo TSun YfalseDIA-BERT: pre-trained end-to-end transformer models for enhanced DIA proteomics data analysis.Data-independent acquisition mass spectrometry (DIA-MS) has become increasingly pivotal in quantitative proteomics. In this study, we present DIA-BERT, a software tool that harnesses a transformer-based pre-trained artificial intelligence (AI) model for analyzing DIA proteomics data. The identification model was trained using over 276 million high-quality peptide precursors extracted from existing DIA-MS files, while the quantification model was trained on 34 million peptide precursors from synthetic DIA-MS files. When compared to DIA-NN, DIA-BERT demonstrated a 51% increase in protein identifications and 22% more peptide precursors on average across five human cancer sample sets (cervical cancer, pancreatic adenocarcinoma, myosarcoma, gallbladder cancer, and gastric carcinoma), achieving 2025-01-01T00:00:00Z2025 Apr2026-06-01T12:57:01.87Z2026-04-08T12:37:21.295ZS-EPMC119970334022924810.1038/s41467-025-58866-4