Matthias Mann Lab
@labs_mann
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The Mann Lab is a pioneer in mass spectrometry-based proteomics. Tweets represent personal views from lab members and Matthias Mann @MPI_Biochem and @UCPH_CPR.
Munich and Copenhagen
Joined December 2018
Thank you Matthias @labs_mann for your visionary leadership and for creating a scientific family that continues to push boundaries. Congratulations from all members and looking forward to the future! #MS #Proteomics #20Years
🎉Congratulations to Matthias Mann on 20 years leading Proteomics & Signal Transduction at MPI of Biochemistry! Two decades of groundbreaking mass spectrometry research and training excellent future scientists. #MS #Proteomics #Science @labs_mann
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Honored to be included in this reflection on 20 excellent years of @MolSystBiol! From our first phosphotyrosine interactome in 2005 to proteome-wide networks - scale has grown exponentially. MS proteomics + AI is transforming systems-level understanding. https://t.co/uQPRNmTA4H
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Elegant chemistry and cryo-EM explain the selective Lys8 ubiquitylation. A clear example of how metabolite sensing and the ubiquitin system intersect.
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Great to see Brenda Schulman’s team post their new bioRxiv paper. MS-based proteomics helped uncover a beautifully simple mechanism: cysteine levels tune metabolism by flipping the inverse stability of LRRC58 and its substrate CDO1. https://t.co/crIxwE0Znz
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Fantastic time at #HUPO2025 in Toronto! Congratulations to our talented Early Career researchers! Proud winners: @OellerMarc 🥇 1st Place Poster, @KathrinKorff 🥈 Runner-up Poster, and @CarolineWeiss30 🎤 3-Minute Thesis award! The future of #proteomics research is bright!
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If you are at HUPO 2025, catch up with our team @labs_mann to hear about our exciting work in single-cell proteomics, immunopeptidomics, spatial proteomics, and the latest advances in mass spectrometry technology!
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In @NatureComms: MS-based proteomics + machine learning to diagnose Lyme neuroborreliosis with 92% accuracy (CSF) and 80% (blood) - paving the way for earlier, less invasive testing. https://t.co/3T9YsJjKfv
nature.com
Nature Communications - Researchers incorporate mass spectrometry-based proteomics and machine learning to assess the potential of a less invasive diagnostic approach for Lyme neuroborreliosis, a...
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Awesome talk by @EricTopol at the Bavarian Academy of Sciences and Humanities (BAdW). A positive and hopeful take on #AI in medicine. Thanks for highlighting #DVP, too 😊
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How the Max Planck Institute is sharing expert skills through multimodal agents @googlecloud
cloud.google.com
The Proteomics Lab Agent assists scientists by simplifying complex scientific procedures through personalized AI guidance, making them easier to execute, while automatically documenting the process.
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AlphaDIA is open-source and free for academic and commercial users. We are currently preparing version 2.0 - stay tuned! #AlphaDIA #Bioinformatics #DeepLearning #MassSpectrometry
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Excited to share AlphaDIA's publication in Nature Biotechnology! Our open-source DIA framework brings deep learning directly to raw MS data with feature-free processing, transfer learning for any PTM, and performance matching top tools. https://t.co/keoFdUc1lG
nature.com
Nature Biotechnology - An open-source platform for data-independent acquisition proteomics adapts predicted libraries to experimental settings.
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How much hands-on lab expertise gets lost? We developed a multimodal AI agent that turns videos into protocols and detects procedural errors. Making science accessible. Great collaboration with #Google. Preprint: https://t.co/JVSWSLEQDR Lead author @patiskowronek explains👇
biorxiv.org
We present a multimodal AI laboratory agent that captures and shares tacit experimental practice by linking written instructions with hands-on laboratory work through the analysis of video, speech,...
In labs, hands-on expertise is often lost because it's not written down. We leverage multimodal AI agents to capture & share it by analyzing video and speech to generate protocols, detect errors, and guide researchers. #AI #TeamMassSpec 📄 Preprint: https://t.co/Nt24iRvSm7 1/🧵
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Congratulations Ericka and all the best for the future!
Let's finish the week with wholehearted Congratulations to Ericka Mae Corazon Itang on her #PhD! 🎉 @labs_mann
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@fabian_theis @hornung_lab @ale__palmaa @can_alioguz @VaryaVarlamova7 @LukasHeumos @GeorgWa 16/ If this interests you: 🔁 Retweet the first post: https://t.co/SWyR6dzMoZ ⭐️ Give our github repo a star https://t.co/nNVCeU1fln ❓ tell us what you are going to do with #scPortrait
github.com
scPortrait is a scalable toolkit to generate single-cell representations from raw microscopy images - MannLabs/scPortrait
1/ Tomorrow’s large scale cross-modality models will further unlock biology, but they need standardized inputs. With @SophiaMaedler, and @Niklas_a_s, we built #scPortrait an @scverse package to turn microscopy images into single-cell image datasets for multimodal modeling
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15/ This work was a fantastic collaboration between @Labs_Mann and @fabian_theis with support from @hornung_lab A big shoutout to all of our co-authors: @ale__palmaa, Altana Namsaraeva, @can_alioguz, @VaryaVarlamova7, @LukasHeumos, Mahima Arunkumar, @GeorgWa
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14/ Bottom line: scPortrait turns microscopy images into a first-class modality for machine learning and multimodal foundation models, alongside RNA and proteomics 🔬💻 🔗 GitHub: https://t.co/nNVCeU1fln 🔗 Preprint:
biorxiv.org
Machine learning increasingly uncovers rules of biology directly from data, enabled by large, standardized datasets. Microscopy images provide rich information on cellular architecture and are...
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13/ Our extensive documentation and tutorials make scPortrait easy to use and accessible. And as part of @scverse it’s compatible with existing tools like scanpy, squidpy, bento-tools or Moscot 🚀🐍 📃 https://t.co/cfFHpRv81R
#OpenSourceTools #Tutorial #CodeDocumentation
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12/ scPortrait already scales: 1️⃣ 120M+ single-cell images from image-based genetic screens 2️⃣ applied on patient-derived datasets to perform AI-driven morphology analysis Refs: 1️⃣ BioRxiv2023 ➡️ https://t.co/Eu1iidXOtv 2️⃣ Nature 2025➡️
nature.com
Nature - High-resolution spatial proteomics were used to map molecular events during hepatocyte stress in pseudotime across all fibrosis stages, recapitulating known disease progression markers and...
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11/ We also ship a benchmark dataset of Golgi morphologies and use it to compare image featurization tools: #ConvNeXt, #SubCell, #CellProfiler
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10/ ✨ Embedding images into transcriptome atlases ✨ We use scPortrait to embed single-cell images from a @10xGenomics Xenium ovarian cancer dataset into the #SCimilarity transcriptome atlas (R2 = 0.65), recovering meaningful cell types
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