Mann Lab
@mannlab.bsky.social
The Mann Lab is a pioneer in mass spectrometry-based proteomics. Posts represent personal views from lab members and Matthias Mann
Matthias Mann is a German physicist and biochemist. He is doing research in the area of mass spectrometry and proteomics.
Source: Wikipedia
Biology
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Chemistry
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Mann Lab
@mannlab.bsky.social
· Jul 1
🎉 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 @mannlab.bsky.social
#MS #Proteomics #Science @mannlab.bsky.social
Thank you Matthias 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
If 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!
Mann Lab
@mannlab.bsky.social
· 11d
The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis - 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 common nervous system infect...
www.nature.com
In 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...
www.nature.com/articles/s41...
Mann Lab
@mannlab.bsky.social
· 13d
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 😊
Mann Lab
@mannlab.bsky.social
· 20d
AlphaDIA is open-source and free for academic and commercial users. We are currently preparing version 2.0 - stay tuned!
#AlphaDIA #Bioinformatics #DeepLearning #MassSpectrometry
#AlphaDIA #Bioinformatics #DeepLearning #MassSpectrometry
Mann Lab
@mannlab.bsky.social
· 20d
AlphaDIA enables DIA transfer learning for feature-free proteomics - Nature Biotechnology
An open-source platform for data-independent acquisition proteomics adapts predicted libraries to experimental settings.
www.nature.com
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...
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...
Mann Lab
@mannlab.bsky.social
· Oct 9
In labs, hands-on expertise is often lost because it's not written down. We leverage multimodal AI agents to capture & share expertise by analyzing video and speech to generate protocols, detect errors, and guide researchers. #AI #TeamMassSpec
📄 Preprint: doi.org/10.1101/2025... 1/🧵
📄 Preprint: doi.org/10.1101/2025... 1/🧵
Multimodal AI agents for capturing and sharing laboratory practice
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, an...
doi.org
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 explains👇
Preprint: www.biorxiv.org/content/10.1...
@patiskowronek.bsky.social explains👇
Reposted by Matthias Mann
Multimodal AI agents for capturing and sharing laboratory practice
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, an...
doi.org
In labs, hands-on expertise is often lost because it's not written down. We leverage multimodal AI agents to capture & share expertise by analyzing video and speech to generate protocols, detect errors, and guide researchers. #AI #TeamMassSpec
📄 Preprint: doi.org/10.1101/2025... 1/🧵
📄 Preprint: doi.org/10.1101/2025... 1/🧵
Mann Lab
@mannlab.bsky.social
· Sep 24
16/
If this interests you:
🔁 Retweet the first post:
bsky.app/profile/mann...
⭐️ Give our github repo a star github.com/MannLabs/scP...
❓ tell us what you are going to do with #scPortrait
If this interests you:
🔁 Retweet the first post:
bsky.app/profile/mann...
⭐️ Give our github repo a star github.com/MannLabs/scP...
❓ tell us what you are going to do with #scPortrait
Mann Lab
@mannlab.bsky.social
· Sep 24
15/
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 Oğuz Can, Varvara Varlamova, Mahima Arunkumar, @lukasheumos.bsky.social, @georgwa.bsky.social
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 Oğuz Can, Varvara Varlamova, Mahima Arunkumar, @lukasheumos.bsky.social, @georgwa.bsky.social
Mann Lab
@mannlab.bsky.social
· Sep 24
scPortrait integrates single-cell images into multimodal modeling
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 accessi...
doi.org
14/
Bottom line:
scPortrait turns microscopy images into a first-class modality for machine learning and multimodal foundation models, alongside RNA and proteomics 🔬💻
🔗 Preprint: doi.org/10.1101/2025...
🔗 GitHub: github.com/MannLabs/scP...
Bottom line:
scPortrait turns microscopy images into a first-class modality for machine learning and multimodal foundation models, alongside RNA and proteomics 🔬💻
🔗 Preprint: doi.org/10.1101/2025...
🔗 GitHub: github.com/MannLabs/scP...
Mann Lab
@mannlab.bsky.social
· Sep 24
13/
Our extensive documentation and tutorials make scPortrait easy to use and accessible.
And as part of @scverse.bsky.social it’s compatible with existing tools like scanpy, squidpy, bento-tools or Moscot 🚀🐍
mannlabs.github.io/scPortrait/i... #OpenSourceTools #Tutorial #CodeDocumentation
Our extensive documentation and tutorials make scPortrait easy to use and accessible.
And as part of @scverse.bsky.social it’s compatible with existing tools like scanpy, squidpy, bento-tools or Moscot 🚀🐍
mannlabs.github.io/scPortrait/i... #OpenSourceTools #Tutorial #CodeDocumentation
Mann Lab
@mannlab.bsky.social
· Sep 24
SPARCS, a platform for genome-scale CRISPR screening for spatial cellular phenotypes
Forward genetic screening associates phenotypes with genotypes by randomly inducing mutations and then identifying those that result in phenotypic changes of interest. Here we present spatially resolv...
www.biorxiv.org
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 ➡️ www.biorxiv.org/content/10.1...
2️⃣ Nature 2025➡️ www.nature.com/articles/s41...
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 ➡️ www.biorxiv.org/content/10.1...
2️⃣ Nature 2025➡️ www.nature.com/articles/s41...
Mann Lab
@mannlab.bsky.social
· Sep 24
11/
We also ship a benchmark dataset of Golgi morphologies and use it to compare image featurization tools: #ConvNeXt, #SubCell, #CellProfiler
We also ship a benchmark dataset of Golgi morphologies and use it to compare image featurization tools: #ConvNeXt, #SubCell, #CellProfiler
Mann Lab
@mannlab.bsky.social
· Sep 24
10/
✨ Embedding images into transcriptome atlases ✨
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
✨ Embedding images into transcriptome atlases ✨
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
Mann Lab
@mannlab.bsky.social
· Sep 24
9/
✨ Morphology defined cell states ✨
Image embeddings generated with scPortrait resolve intra- vs extratumoral macrophages with distinct morphologies, linked to anti-inflammatory vs fibroblast-like programs
✨ Morphology defined cell states ✨
Image embeddings generated with scPortrait resolve intra- vs extratumoral macrophages with distinct morphologies, linked to anti-inflammatory vs fibroblast-like programs
Mann Lab
@mannlab.bsky.social
· Sep 24
8/
✨ Transcriptomes from images ✨
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
✨ Transcriptomes from images ✨
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
Mann Lab
@mannlab.bsky.social
· Sep 24
7/
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
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
Mann Lab
@mannlab.bsky.social
· Sep 24
6/
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.
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.
Mann Lab
@mannlab.bsky.social
· Sep 24
5/
The scPortrait pipeline transforms raw input images step by step:
• stitch FOVs
• segment & extract cells
• output standardized .h5sc single-cell image datasets
From messy pixels → inputs ready for training 🖥️
The scPortrait pipeline transforms raw input images step by step:
• stitch FOVs
• segment & extract cells
• output standardized .h5sc single-cell image datasets
From messy pixels → inputs ready for training 🖥️
Mann Lab
@mannlab.bsky.social
· Sep 24
4/
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 🔬microscopy images into a reusable resource for integrative cell modeling
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 🔬microscopy images into a reusable resource for integrative cell modeling
Mann Lab
@mannlab.bsky.social
· Sep 24
3/
Microscopy images are:
📈 easy to acquire across scales (organism → subcellular)
🖥️ information-rich (cellular architecture, tissue structure, perturbation responses)
= 🚀 ideal fuel for foundation models of cell behavior
Microscopy images are:
📈 easy to acquire across scales (organism → subcellular)
🖥️ information-rich (cellular architecture, tissue structure, perturbation responses)
= 🚀 ideal fuel for foundation models of cell behavior
Mann Lab
@mannlab.bsky.social
· Sep 24
2/
AI has had major breakthroughs (#alphafold #chatgpt) & computational models can now detect patterns in complex datasets without external guidance 🧠🖥️
🧬 biological datasets often contain entangled information making them complex to interpret →🧠🖥️ + 🧬 = unlock new biology
AI has had major breakthroughs (#alphafold #chatgpt) & computational models can now detect patterns in complex datasets without external guidance 🧠🖥️
🧬 biological datasets often contain entangled information making them complex to interpret →🧠🖥️ + 🧬 = unlock new biology