AI-Ready Mass Spectrometry (AIR-MS)

Unlocking Hidden Proteomics Data: Turning In-house MS Data into AI-ready Resources
MassNet species overview

MassNet aims to build a large-scale, diverse, and standardized AI-ready proteomics resource by transforming valuable proteomics datasets generated worldwide into reusable resources for AI model development and benchmarking.

We have established the first version of MassNet, an AI-ready proteomics resource comprising ∼28,000 DDA-MS files and ∼46,000 DIA-MS files. The MassNet-DDA [1] and its associated work have been accepted in principle by Nature Methods.

We welcome contributions from proteomics laboratories worldwide.

1. Dataset Requirements

We currently prioritize global proteomics datasets. Specialized datasets, including PTM proteomics, immunopeptidomics, and metaproteomics, are also welcome, with additional metadata required for downstream processing and database searching.

Item Requirements
MS Acquisition Label-free DDA and DIA
Species No restriction
Sample Type Biological research samples
Mass spectrometers
  • Thermo Fisher: Q Exactive series (Q Exactive HF, Q Exactive HF-X, and Q Exactive UHMR); Orbitrap Tribrid series (Orbitrap Fusion, Orbitrap Fusion Lumos, Orbitrap Eclipse Tribrid, Orbitrap IQ-X Tribrid, and Orbitrap Ascend Tribrid); Orbitrap Exploris series (e.g., Orbitrap Exploris 120, 240, and 480); Orbitrap Astral series (e.g., Astral, and Astral Zoom); Orbitrap Excedion Pro.
  • SCIEX: ZenoTOF series (7600, 7600+, and 8600); TripleTOF 6600, 6600+
  • Bruker: timsTOF series (timsTOF Pro, Pro 2, SCP, HT, Ultra, Ultra 2, and timsUltra AIP)

2. Required Metadata

Please provide the following experimental information for each dataset. Additional details may be required for specialized datasets to support appropriate FASTA/database selection and downstream database searching.

Required Information Example
Raw file name e.g., sample_001.raw
Dataset description e.g., Human plasma proteomics dataset
Species e.g., Homo sapiens
Biological condition e.g., Benign tissue
Instrument e.g., Orbitrap Exploris 480
Acquisition mode e.g., DDA
Digestion e.g., Trypsin
Additional information (if applicable) e.g., PTM type / HLA-I or HLA-II / metaproteomics sample source

Metadata template: Download here

3. Excluded Data

The following datasets are not required:

❌ QC samples
❌ System suitability test samples
❌ Instrument performance monitoring runs

4. Data Submission

1. Prepare Data

  • Raw MS files
  • Corresponding metadata information

2. Upload Data

Upload raw files to your preferred secure storage platform (e.g., Google Drive, Baidu disk) and share the download link with us.

3. Data Processing

Our team will perform: metadata harmonization, standardized processing, quality control, annotation, and conversion into AI-ready formats.

5. Contact

For any questions, please contact us atajun@westlake.edu.cn

6. Reference

[1] A, J., Zhang, X., Zhang, XF. et al. MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing. bioRxiv; doi: https://doi.org/10.1101/2025.06.20.660691.