We congratulate @georgwa.bsky.social from the @mannlab.bsky.social on his sucessful #PhD defense!
27.11.2025 15:17 β π 0 π 1 π¬ 0 π 0@mannlab.bsky.social
The Mann Lab is a pioneer in mass spectrometry-based proteomics. Posts represent personal views from lab members and Matthias Mann
We congratulate @georgwa.bsky.social from the @mannlab.bsky.social on his sucessful #PhD defense!
27.11.2025 15:17 β π 0 π 1 π¬ 0 π 0Honored 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. Exciting times!
embopress.org/doi/pdf/10.1...
Elegant chemistry and cryo-EM explain the selective Lys8 ubiquitylation. A clear example of how metabolite sensing and the ubiquitin system intersect.
17.11.2025 10:27 β π 1 π 0 π¬ 0 π 0Great to see Brenda Schulmanβs 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.
www.biorxiv.org/content/bior...
Fantastic time at #HUPO2025 in Toronto! Congratulations to our talented Early Career researchers! Proud winners: Oeller Marc Oellerπ₯ 1st Place Poster, Kathrin Korff π₯ Runner-up Poster, and @carolineweiss.bsky.social π€ 3-Minute Thesis award! The future of #proteomics research is bright!
13.11.2025 12:01 β π 16 π 1 π¬ 0 π 0If you are at HUPO 2025, catch up with our team @mannlab.bsky.social to hear about our exciting work in single-cell proteomics, immunopeptidomics, spatial proteomics, and the latest advances in mass spectrometry technology!
07.11.2025 13:20 β π 8 π 1 π¬ 0 π 0In Nature Communications: MS-based proteomics + machine learning to diagnose Lyme neuroborreliosis with 92% accuracy (CSF) and 80% (blood) - paving the way for earlier, less invasive testing.
www.nature.com/articles/s41...
Awesome talk by @erictopol.bsky.social at the Bavarian Academy of Sciences and Humanities (BAdW). A positive and hopeful take on #AI in medicine. Thanks for highlighting #DVP, too π
29.10.2025 08:58 β π 5 π 0 π¬ 0 π 0AlphaDIA is open-source and free for academic and commercial users. We are currently preparing version 2.0 - stay tuned!
#AlphaDIA #Bioinformatics #DeepLearning #MassSpectrometry
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.
www.nature.com/articles/s41...
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: www.biorxiv.org/content/10.1...
@patiskowronek.bsky.social explainsπ
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If this interests you:
π Retweet the first post:
bsky.app/profile/mann...
βοΈ Give our github repo a star github.com/MannLabs/scP...
β tell us what you are going to do with #scPortrait
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This work was a fantastic collaboration:
@mannlab.bsky.social
@fabiantheis.bsky.social
@v-hornung.bsky.social
A big shoutout to all of our co-authors: Alessandro Palma,
Altana Namsaraeva, Ali OΔuz Can, Varvara Varlamova, Mahima Arunkumar, @lukasheumos.bsky.social, @georgwa.bsky.social
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Bottom line:
scPortrait turns microscopy images into a first-class modality for machine learning and multimodal foundation models, alongside RNA and proteomics π¬π»
π Preprint: doi.org/10.1101/2025...
π GitHub: github.com/MannLabs/scP...
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Our extensive documentation and tutorials make scPortrait easy to use and accessible.
And as part of @scverse.bsky.social itβs compatible with existing tools like scanpy, squidpy, bento-tools or Moscot ππ
mannlabs.github.io/scPortrait/i... #OpenSourceTools #Tutorial #CodeDocumentation
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scPortrait already scales:
1οΈβ£ 120M+ single-cell images from image-based genetic screens
2οΈβ£ applied on patient-derived datasets to perform AI-driven morphology analysis
Refs:
1οΈβ£ BioRxiv2023 β‘οΈ www.biorxiv.org/content/10.1...
2οΈβ£ Nature 2025β‘οΈ www.nature.com/articles/s41...
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We also ship a benchmark dataset of Golgi morphologies and use it to compare image featurization tools: #ConvNeXt, #SubCell, #CellProfiler
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β¨ Embedding images into transcriptome atlases β¨
We use scPortrait to embed single-cell images from a @10xgenomics.bsky.social Xenium ovarian cancer dataset into the #SCimilarity transcriptome atlas (R2 = 0.65), recovering meaningful cell types
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β¨ Morphology defined cell states β¨
Image embeddings generated with scPortrait resolve intra- vs extratumoral macrophages with distinct morphologies, linked to anti-inflammatory vs fibroblast-like programs
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β¨ Transcriptomes from images β¨
Using optimal transport + flow matching, scPortrait generates gene expression directly from CODEX images, capturing canonical marker expression like TCL1A in germinal centers in the tonsil
#CODEX #flowmatching #OT
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With standardized single-cell image datasets in place, the key question is: what new biology can we unlock?
We highlight three use-cases for scPortrait
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The new .h5sc format provides fast random access to single-cell images for ML training.
It follows #FAIR data principles (findable, accessible, interoperable, reusable) and integrates with @scverse.bsky.social tools via AnnData.
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The scPortrait pipeline transforms raw input images step by step:
β’ stitch FOVs
β’ segment & extract cells
β’ output standardized .h5sc single-cell image datasets
From messy pixels β inputs ready for training π₯οΈ
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Problem: microscopy images are messy, fragmented, and hard to use for ML
Solution: scPortrait standardizes them into a new .h5sc single-cell image format turning π¬microscopy images into a reusable resource for integrative cell modeling
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Microscopy images are:
π easy to acquire across scales (organism β subcellular)
π₯οΈ information-rich (cellular architecture, tissue structure, perturbation responses)
= π ideal fuel for foundation models of cell behavior
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AI has had major breakthroughs (#alphafold #chatgpt) & computational models can now detect patterns in complex datasets without external guidance π§ π₯οΈ
𧬠biological datasets often contain entangled information making them complex to interpret βπ§ π₯οΈ + 𧬠= unlock new biology
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Tomorrowβs large scale cross-modality models will further unlock biology, but they need standardized inputs. With @sophia-maedler.bsky.social & @nik-as.bsky.social, we built #scPortrait, @scverse.bsky.social package to turn microscopy images into single-cell image datasets for multimodal modeling
Our preprint on scPortrait is out! We built a framework + format to turn microscopy into standardized single-cell image datasets. #scPortrait scales >100M cells, integrates with @scverse.bsky.social, & enables cross-modality modeling from morphology to transcriptomics
doi.org/10.1101/2025...
Congratulations on the inaugural of #AITHYRA, the new Biomedical AI institute in Vienna. Thank you for the invitation to speak at the symposium and the fascinating discussions on AI Γ proteomics. #AIforLifeScience
15.09.2025 08:10 β π 4 π 0 π¬ 0 π 0Thanks CPR, reNEW, @ucph.bsky.social
Full story:
www.sciencedirect.com/science/arti...