We study cancer and immunology, combining experimental biology with high-throughput technology, bioinformatic methods and machine learning. Our work is interdisciplinary and collaborative. We are equally committed to biological discovery and to advancing medicine.

🚀 Check out the paper, dataset, and computational methods (open access | open data | open source):.🧬Dataset: 💻 Code: 📑Paper: Feedback & suggestions are very welcome. (9/9).

Join millions who have switched to Grok.

🤝Teamwork by: Peter Traxler*, Stephan Reichl*, Lukas Folkman, Lisa Shaw, Victoria Fife, Amelie Nemc, Djurdja Pasajlic, Anna Kusienicka, Daniele Barreca, Nikolaus Fortelny, André Rendeiro, Florian Halbritter, Wolfgang Weninger, Thomas Decker, Matthias Farlik, Christoph Bock (8/9)

🗺️In summary, this study provides a blueprint of epigenetic & transcriptional dynamics and regulator functions underlying macrophage immune responses. We found it particularly useful to combine and integrate multi-omics time-series with high-content CRISPR screening. (7/9)

💡Biological detail: EP300-mediated repression of interferon-stimulated genes (ISGs), validated genetically & pharmacologically. Proposed mechanism: The histone acetyltransferase EP300 counteracts HDAC activity required for BRD4 availability for transcription elongation. (6/9)

🤖We used machine learning to infer functional similarity maps of transcriptional regulators from the CROP-seq data, establishing a broadly applicable method to dissect transcriptional programs. (5/9)

✂️To disentangle causes and consequences, we performed high-content CRISPR screening (CROP-seq + CITE-seq) to perturb 135 regulators during Listeria infection. Our hits include: PU.1, JAK-STAT proteins, splicing factors (SFPQ, SF3B1) & epigenetic regulators (EP300, SMC1A). (4/9)

🧬Integrative analysis revealed strong differences between interferon-driven (IFN-β/γ) and pathogen-driven (Listeria/LPS) trajectories. Many immune genes showed "epigenetic potential": pre-established open chromatin ready for rapid expression upon stimulation. #Epigenetics (3/9)

🦠Pathogens & cytokines trigger macrophage receptors and induce immune gene expression. We challenged mouse macrophages (BMDMs) with 6 immune stimuli (Listeria, LCMV, Candida, LPS, IFN-β, IFN-γ) and profiled genes (RNA-seq) and chromatin (ATAC-seq) over six time points. (2/9)

🛡️How do macrophages tailor their defenses to different pathogens? Our new paper in @CellSystems combines dense multi-omics time series with high‐content CRISPR screens (CROP-seq) to map the regulatory landscape underlying macrophage immune responses. #Immunity #Screening (1/9)

🤝 Great collaboration between @BockLab (@muronglizi, Animesh, Jake), @gxrlab (@nonchevk, @gxr), and pathologist Viktor Kölzer. SpotWhisperer is presented at #ICML25 FM4LS workshop – visit our poster this Saturday (19 July 2025) if you are interested & attending ICML. (6/6).

🚀 Next steps: (1) Interactive SpotWhisperer web application; (2) tri-modal joint embedding of spatial transcriptomics, textual annotations, and images; (3) validation across a broad range of histopathological applications. What would you like to see? (5/6).

🧑‍💻 In summary, SpotWhisperer integrates spatial transcriptomes into histopathology, bypassing high costs (we infer gene expression from H&E stains) and complexity (we built a chat interface). Check out our preprint: & project: (4/6).

🔍 While vision language models (VLMs) for digital pathology converse about H&E images as a whole, SpotWhisperer provides fine-grained, spot-level resolution. Consequently, SpotWhisperer outperformed SOTA VLMs (PLIP, CONCH) in the prediction of tumor regions and cell types. (3/6)

⚙️ Our SpotWhisperer method predicts spatial transcriptomes from standard H&E images with DeepSpot, and it uses CellWhisperer transcriptome-text embeddings for natural-language conversations about the cells and their transcriptomes. (2/6)

🔬 Toward histopathology 2.0: spatial transcriptomes inferred from routine diagnostic H&E images + a chat interface for cell-resolution histopathology through English language. (1/6)

RT @BockLab: AI in medicine ready for takeoff! 🤖🚁 We flew a drone through the Institute of Artificial Intelligence @MedUni_Wien. Join us fo….

AI in medicine ready for takeoff! 🤖🚁 We flew a drone through the Institute of Artificial Intelligence @MedUni_Wien. Join us for the trip and watch our team at "work". Credits: @muronglizi, @QuantifiedRob, @R_Bednarsky & the entire crew. #AI #biomedicine #innovation #makingof

Check out the pictures & research updates of all groups at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences. Link to our Research Report: PDF: Great photography by Klaus Pichler & Florian Rainer.

CeMM's new Research Report is online - a piece of art as always (link below). Each group selected a mathematical formula to symbolize their research and visualized it in a live group picture. We picked Shannon entropy, as biomedicine is all about information (and sometimes messy)

If you are considering in vivo screens - for example in mouse models of human diseases - please also have a look at our recent News&Views accompanying a very detailed and helpful protocol on that topic:.