singjc/redeem

Repository for Deep Learning Models for Mass Spectrometry written in Rust

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/ 100
Emerging

This tool helps analytical chemists and proteomics researchers predict key properties of peptides from mass spectrometry data. You input peptide sequences and it provides predicted retention times (RT), collision cross-sections (CCS), and MS2 fragment ion intensities. It's designed for scientists working with mass spectrometers who need to interpret or validate their experimental results.

Use this if you need to predict peptide properties like retention time or collision cross-section, or rescore peptide-spectrum matches (PSMs) in your mass spectrometry experiments.

Not ideal if you are looking for a standalone graphical user interface for general proteomics data analysis, as this is primarily a programmatic library.

proteomics mass-spectrometry peptide-analysis analytical-chemistry bioinformatics
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 9 / 25

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Stars

16

Forks

2

Language

Rust

License

BSD-3-Clause

Last pushed

Feb 22, 2026

Commits (30d)

0

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