ArticleNature biotechnology2026
AlphaDIA enables DIA transfer learning for feature-free proteomics.
Article in Nature biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Proteomic investigation of signaling dynamics: from static maps to network rewiring.Bioscience reports · 2026Review
- Instrument-Software Synergy in Proteomics: Systematic Evaluation across Mass Spectrometry Platforms, Search Engines, and Rescoring Methods.Journal of proteome research · 2026Article
- Full-DIA enables complete single-cell proteomics from diaPASEF using deep learning.Genome biology · 2026Article
- Insights into the Regulation of Indigo Production in an EngineeredFoods (Basel, Switzerland) · 2026Article
- Multi-Omics for Mothers and Infants (MOMI) Consortium: a global initiative to study adverse pregnancy outcomes.Journal of global health · 2026Article
- Transfer learning in DeepLC improves LC retention time prediction across substantially different modifications and setups.Nature communications · 2026Article
- Integrating Metabolomics and Proteomics to Reveal the Regulatory Network Governing the Natural Variation in Rice Seed Germination Rate.Plants (Basel, Switzerland) · 2026Article
- Data-independent acquisition-based quantitative proteomics in plants.Frontiers in plant science · 2026Review
- Benchmark for Quantitative Global and Redox Proteomics Analysis by Combining Protein-Aggregation Capture and Data Independent Acquisition.Analytical chemistry · 2025Article
- Increasing mass spectrometry throughput using time-encoded sample multiplexing.bioRxiv : the preprint server for biology · 2025Article
- Open-Source and FAIR Research Software for Proteomics.Journal of proteome research · 2025Review
- Recent Advances in Mass Spectrometry-Based Bottom-Up Proteomics.Analytical chemistry · 2025Review
- A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis.Journal of proteome research · 2025Article
- Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.Molecular & cellular proteomics : MCP · 2024Article
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Authors and funding
16 authors.
Funding
Abstract
The scale of data generated for mass-spectrometry-based proteomics and modern acquisition strategies poses a challenge to bioinformatic analysis. Search engines need to make optimal use of the data for biological discoveries while remaining statistically rigorous, transparent and performant. Here we present alphaDIA, a modular open-source search framework for data-independent acquisition (DIA) proteomics. We developed a feature-free identification algorithm that performs machine learning directly on the raw signal and is particularly suited for detecting patterns in data produced by time-of-flight instruments. Benchmarking demonstrates competitive identification and quantification performance. While the method supports empirical spectral libraries, we propose a search strategy named DIA transfer learning that uses fully predicted libraries. This entails continuously optimizing a deep neural network for predicting machine-specific and experiment-specific properties, enabling the generic DIA analysis of any post-translational modification. AlphaDIA provides a high performance and accessible framework running locally or in the cloud, opening DIA analysis to the community.
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