@wilhelm_compms

TT Professor of Computational Mass Spectrometry at the Technical University of Munich. Focusing on mass spectrometry-based proteomics. @proteomicsdb @msaid_de

 Germany
Joined September 2021
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  • Following636
  • Followers1.2K
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Wilhelm Lab has arrived at #HUPO2026 in Singapore! Catch us presenting across five talks/posters spanning databases, de novo peptide sequencing, Match-Between Run, and crop proteomics — swing by and say 👋 or scan the QR code to learn more about our work.
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Prosit-MultiFrag, a model predicting spectra for UVPD, ECD, ETciD & EID, is out 🚀 🔗 nature.com/articles/s41592-0… Great collaboration with Shabaz Mohammed & Nikita Levin. Try it via Koina koina.proteomicsdb.org and Oktoberfest: github.com/wilhelm-lab/oktob… #Proteomics #MassSpectrometry

Integration of alternative fragmentation techniques into standard LC-MS workflows using a single...

Nature Methods - An integrated mass spectrometry platform enabling automated collision-, electron- and photon-based fragmentation techniques is presented. A deep learning-based model trained to...

nature.com
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You want easy access, integration, and reuse of deep learning models?🤖 You want to plug new models into your pipelines without pain?🔌 Koina is your solution🚀rdcu.be/ePqaA An open and decentralized model hub — built to make ML in proteomics usable🌐 #proteomics #AI
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After a long journey, we’re thrilled to share our new preprint! 🎉 🔬 Prosit-PTM leveraging ProteomeTools-PTM and novel data augmentation to enable zero-shot prediction 👉 Boosts PTM site localization, histone peptide IDs, and even modifications on HLA peptides #AI #Proteomics
bioRxiv Bioinfo@biorxiv_bioinfo10 Nov 2025
Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM biorxiv.org/content/10.1101/… #biorxiv_bioinfo

Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM

Post-translational modifications (PTMs) are critical regulators of protein function, yet confidently identifying and localizing PTM sites across proteomes remains a challenging task. Integrating...

biorxiv.org
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Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM biorxiv.org/content/10.1101/… #biorxiv_bioinfo

Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM

Post-translational modifications (PTMs) are critical regulators of protein function, yet confidently identifying and localizing PTM sites across proteomes remains a challenging task. Integrating...

biorxiv.org
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🚀 Join us for a PhD in AI & proteomics! Work on confidence prediction for fine-tuned AI peptide property models with applications in single-cell proteomics. 🔬 Apply by Nov 30 2025: 👉 tinyurl.com/5csmhw52 #PhD #AI #Proteomics #MachineLearning #TUM #MarieCurie #Research
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🚨 New paper drop! Prosit-XL by Mostafa from @PROTrEIN_ITN! 🔬 Accurately predicts fragment intensities 🧬 For cleavable & non-cleavable linkers 📈 Boosts PPI discovery 🧠 Smarter rescoring avoids FDR inflation 👉 nature.com/articles/s41467-0… #Proteomics #MassSpec #AI #Bioinformatics

Prosit-XL: enhanced cross-linked peptide identification by fragment intensity prediction to study...

Nature Communications - Cross-linking mass spectrometry studies protein interactions and structures but struggles with identifying crosslinked peptides. Here, the authors present Prosit-XL, a...

nature.com
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Good things­ take time🎆 This is certainly true for #CHIMERYS . First prototype implemented in 2019 for DDA only. New with full support for DIA and PRM as well. So happy to finally see it published in #naturemethods Great accomplishment by @msaid_de
MSAID
@msaid_de22 Apr 2025
🚨 New in @naturemethods #CHIMERYS has already transformed #proteomics since 2022, powering DDA, DIA & PRM analysis in a single workflow. Wanna know how CHIMERYS works? 👉 nature.com/articles/s41592-0… #TeamMassSpec #NatureMethods #ASMS2025 🧪🔬 1/7

Unifying the analysis of bottom-up proteomics data with CHIMERYS

Nature Methods - CHIMERYS is a spectrum-centric and data acquisition method-agnostic algorithm for the analysis of MS2 spectra. It is capable of deconvoluting any MS2 spectrum, regardless of...

nature.com
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#HUPO2024 starts tomorrow and the Terrific TUM Team is ready! Kusterlab, Wilhelmlab (@wilhelm_compms), Leelab (@msleemslab) and BayBioMS (@BayBioMS) have printed their posters and prepared their talks, and we're very excited for the next days. See you in Dresden!
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You have a strong background in bioinformatics🖥️, data science📈, machine learning, and multi omics? You want to do a PhD👩‍🎓facilitating non-clinical safety assessment? If so, come and join our ProteomicsDB team. mls.ls.tum.de/compms/job-off…
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📊Never heard about rescoring in proteomics? Check our latest manuscript on rescoring search engine results in proteomics using machine and deep learning and our perspective on it for users and developers📈 mcponline.org/article/S1535-… #proteomics #machinelearning #deeplearning

Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property...

In briefRescoring peptide spectrum matches by integrating predicted peptide properties, such as MS/MS intensity and retention time, substantially boosts the number of confidently identified peptides...

mcponline.org
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Mathias Wilhelm retweeted
Maria Martin@martinmariaj5 Mar 2024
If you value UniProt, please help us to capture this in this survey!
UniProt@uniprot5 Mar 2024
Is UniProt valuable to your research work? Please complete our survey, measuring the value and impacts of open science to the research community. ec.europa.eu/eusurvey/runner… #OpenData #OpenScience
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#proteomics ⚖️, #datascience 📊 or #programmers 🧑‍💻? We are looking to fill a staff scientist position centered around ProteomicsDB. More details available here: mls.ls.tum.de/en/compms/job-…
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First paper in 2024 is out. Spectralis for de novo peptide sequencing nature.com/articles/s41467-0…. Awesome collaboration with @gagneurlab spearheaded by Daniela Klaproth-Andrade.

Deep learning-driven fragment ion series classification enables highly precise and sensitive de...

Nature Communications - Accurate and high-throughput sequencing methods for proteins are lacking. Here the authors report Spectralis which improves de novo peptide sequencing using a convolutional...

nature.com
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Hey, #BSPREUPA2023 folks! We are coming to #BSPREUPA2023 in Newcastle with a poster and a talk! Looking forward to meeting, discussing and doing new collaborations! 🤩 #cropproteomeengine
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Mathias Wilhelm retweeted
MS Lee Lab@msleemslab8 Jun 2023
Time flies! Last day at #ASMS2023 we are excited to reveal our final meters of posters by @leelab and @wilhelm_compms, showcasing the Prosit PTM model and its impact on citrullination identification accuracy. Don't miss out on this finale! #TTTT #TUM
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Mathias Wilhelm retweeted
Ralf Gabriels@RalfGabriels5 Jun 2023
At #ASMS2023 and want to discuss or learn about #OpenMS and about #MachineLearning? Join the @OpenMSTeam (Samuel Wein & @JeongKyowon), @sgessulat, @wilhelm_compms, and me at the #BioinformaticsHub for sessions at 10:30 and at 12:30. Full schedule 👇github.com/CompMS/Overview/w…

ASMS 2023

General Information about CompMS Activities. Contribute to CompMS/Overview development by creating an account on GitHub.

github.com
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Less than 2 weeks left to register and submit abstracts to the BSPR-EUPA 2023 conference in Newcastle! Deadline May 21st! register here: conferences.ncl.ac.uk/bspr-e… #proteomics @EuPAProteomics @UKBspr
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Mathias Wilhelm retweeted
Goh Lab@GohLab8 May 2023
Prosit Oktoberfest & Koiner for #ML predicted peptide identification #proteomics #aohupo2023 #aoapo2023 #wilhelmlab #ms #maxquant @wilhelm_compms
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Mathias Wilhelm retweeted
MSAID
@msaid_de19 Apr 2023
Join us at the #ASMS2023 Conference in Houston in June. Visit our booth #707, where we will be presenting major updates to CHIMERYS, our intelligent search algorithm for proteomics. See you in Texas! msaid.de/conferences/asms202… #TeamMassSpec #TeamProteomics
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