Excited to share our new Prosit-PTM paper is out! A deep learning model that predicts MS2 spectra and Retention time for modified peptides, using chemically informed encodings and data augmentation based on amino acid substitution to learn general rules for how PTMs affect spectra.

Did you ever come across a phosphosite in your proteomics data for which nothing was known? - I bet so! We have developed a new strategy termed "potency coherence analysis" that leverages the drug potency dimension in decryptM to decode the kinases that shape the human phosphoproteome. Read more:

Exited to share our latest work! Out now in @natcomms.nature.com Koina aims to transform how #proteomics uses machine learning. You no longer need to be a tech wizard to use ML and now can easily run #ML models. Integrated with FragPipe, Skyline and EncyclopeDIA! www.nature.com/articles/s41...

Excited our paper is out in Cell @cp-cell.bsky.social! 🧬⚡ DNA photo-crosslinking proteomics in living cells 🎯 Pinpoints protein-DNA interactions to single amino acids 🌎 Globally quantifies DNA binding for >1800 proteins at a timescale of minutes 🔗 www.cell.com/cell/fulltex... 🧵