MassSpecGym: A benchmark for the discovery and identification of molecules
Abstrak
The discovery and identification of molecules in biological and environmental samples is crucial for advancing biomedical and chemical sciences. Tandem mass spectrometry (MS/MS) is the leading technique for high-throughput elucidation of molecular structures. However, decoding a molecular structure from its mass spectrum is exceptionally challenging, even when performed by human experts. As a result, the vast majority of acquired MS/MS spectra remain uninterpreted, thereby limiting our understanding of the underlying (bio)chemical processes. Despite decades of progress in machine learning applications for predicting molecular structures from MS/MS spectra, the development of new methods is severely hindered by the lack of standard datasets and evaluation protocols. To address this problem, we propose MassSpecGym -- the first comprehensive benchmark for the discovery and identification of molecules from MS/MS data. Our benchmark comprises the largest publicly available collection of high-quality labeled MS/MS spectra and defines three MS/MS annotation challenges: de novo molecular structure generation, molecule retrieval, and spectrum simulation. It includes new evaluation metrics and a generalization-demanding data split, therefore standardizing the MS/MS annotation tasks and rendering the problem accessible to the broad machine learning community. MassSpecGym is publicly available at https://github.com/pluskal-lab/MassSpecGym.
Penulis (30)
Roman Bushuiev
Anton Bushuiev
Niek F. de Jonge
Adamo Young
Fleming Kretschmer
Raman Samusevich
Janne Heirman
Fei Wang
Luke Zhang
Kai Dührkop
Marcus Ludwig
Nils A. Haupt
Apurva Kalia
Corinna Brungs
Robin Schmid
Russell Greiner
Bo Wang
David S. Wishart
Li-Ping Liu
Juho Rousu
Wout Bittremieux
Hannes Rost
Tytus D. Mak
Soha Hassoun
Florian Huber
Justin J. J. van der Hooft
Michael A. Stravs
Sebastian Böcker
Josef Sivic
Tomáš Pluskal
Akses Cepat
- Tahun Terbit
- 2024
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓