ArticleNature communications2025
Koina: Democratizing machine learning for proteomics research.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
23 citing papers in PubMed.
- Label-Free Targeted Proteomics Data Analysis Workflow Selection - Benchmarking AI-based and Data-Driven Approaches.Molecular & cellular proteomics : MCP · 2026Article
- Article
- Identification of the plant mitochondrial OrfX protein: A mass spectrometry approach.FEBS letters · 2026Article
- Proteomic Biomarkers in VTE: From Discovery to Clinical Translation.Journal of clinical medicine · 2026Review
- DDA-BERT: end-to-end training for data-dependent acquisition mass spectrometry-based proteomics.Nature communications · 2026Article
- Review
- Rapid photo-crosslinking in living cells reveals protein-nucleic acid dynamics on a timescale of minutes.Nucleic acids research · 2026Article
- Integration of alternative fragmentation techniques into standard LC-MS workflows using a single deep learning model enhances proteome coverage.Nature methods · 2026Article
- Advances in Mass Spectrometry Instrumentation and Methodology for Analysis of Alternative Protein Isoforms.Journal of mass spectrometry : JMS · 2026Review
- Modanovo: A Unified Model for Post-translational Modification-Aware De Novo Sequencing Using Experimental Spectra From In Vivo and Synthetic Peptides.Molecular & cellular proteomics : MCP · 2026Article
- Paleo-proteomic analysis of Iron Age dental calculus provides direct evidence of Scythian reliance on ruminant dairy.PloS one · 2026Article
- Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.Nature communications · 2025Article
- Alternate RNA decoding results in stable and abundant proteins in mammals.bioRxiv : the preprint server for biology · 2025Article
- FastSpel: A Method for Fast Spectral Library Generation.Journal of proteome research · 2025Article
- Article
- Carafe enables high qualitybioRxiv : the preprint server for biology · 2025Article
- Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study protein interactions and structures.Nature communications · 2025Article
- The microbiologist's guide to metaproteomics.iMeta · 2025Review
- Peptide Property Prediction for Mass Spectrometry Using AI: An Introduction to State of the Art Models.Proteomics · 2025Review
- ProSIMSIt: The Best of Both Worlds in Data-Driven Rescoring and Identification Transfer.Journal of proteome research · 2025Article
Corrections and comments
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Authors and funding
25 authors.
Funding
Abstract
Recent developments in machine learning (ML) and deep learning have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML models are regularly published, the rate at which the community adopts these models is slow. This is in part due to a lack of findability and accessibility of these models as well as the technical challenges involved in incorporating these models into data analysis pipelines and demonstrating their reusability for end-users. Here we show Koina, an open-source decentralized and online-accessible model repository to facilitate publication of ML models. Koina enables ML model usage via an easy-to-use online interface, facilitating the integration of ML models in data analysis pipelines. Using the widely used FragPipe computational platform as an example, we demonstrate how Koina can be integrated with existing proteomics software tools and how these integrations improve data analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.