New in DeepLC! Ability to deal with wild, weird, and wobbly LC setups or peptide modifications. This ability is possible with transfer learning; where only a minimal amount of training peptides are needed for accurate retention time predictions.

www.biorxiv.org/content/10.1...

What a great tool. I use DeepLC in #quantms, in all our relanalysis, proteogenomics, and it works out of the box. Great work from @robbinbouwmeester.bsky.social and compomics team

Excited to share our new paper “MHCquant2 refines immunopeptidomics tumor antigen discovery” in Genome Biology!
An open-source @nf-co.re workflow using OpenMS, DeepLC & MS²PIP boosts peptide ID & sensitivity. Scalable, reproducible & ready for large-scale immunopeptidomics.

👉 rdcu.be/eHFTZ

So you’re saying ChronoLogger-DeepLC-Prosit-PRM is the way.

🚀 #quantms 1.7.0 released (#Caracas)

MS2 transfer learning, #DeepLC, #MS2PIP, #AlphaPeptDeep, advanced rescoring, and onsite phosphorylation scoring are here! 🧵

> github.com/bigbio/quant...
> docs.quantms.org/en/latest/in...
> quantms.org/home

#quantms #proteomics #massspectrometry

Cool! Small comment, indeed the hela_hf model can predict from TMT-labelled peptides, it needs to extrapolate a lot. Best is probably to use this model: github.com/RobbinBouwme...

#quantms-rescoring received a major upgrade, making it more powerful and adaptable across datasets and acquisition strategies.

- MS2 transfer learning across instruments & setups (AlphaPeptDeep)
- Improved model #DeepLC and #MS2PIP handling & fixed rescoring ranges

#machinelearning #proteomics

DeepLC introduces transfer learning for accurate LC retention time prediction and adaptation to substantially different modifications and setups https://www.biorxiv.org/content/10.1101/2025.06.01.657225v1

Or even better, use the transfer learning ability of DeepLC with a good base model (e.g., the one above)

DeepLC introduces transfer learning for accurate LC retention time prediction and adaptation to substantially different modifications and setups https://www.biorxiv.org/content/10.1101/2025.06.01.657225v1

DeepLC introduces transfer learning for accurate LC retention time prediction and adaptation to substantially different modifications and setups [new]