iiinova — where your digital self keeps evolving

Reposted by Moritz Gerstung

Deutsches Krebsforschungszentrum (DKFZ) @dkfz.bsky.social · 18/03/2026

Do you want to do your #postdoc in #cancerresearch with the most prestigious fellowship in Europe? Apply to DKFZ #MSCA MasterClasses by May 18. 26 Projects in cancer research including #cellandmolecularbiology #genomics #bioinformatics #immunology. @horizoneu.bsky.social 👉Apply here: t1p.de/nx6tu

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Reposted by Moritz Gerstung

zaira seferbekova 👾 @zaira-sef.bsky.social · 06/10/2025

🚨 new glioblastoma preprint alert! we present the first spatially resolved single cell atlas comparing radionecrotic changes (RN) and recurrent IDH-wildtype glioblastoma (GB) –– shedding light on a long-standing diagnostic challenge. 🧵 1/

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Moritz Gerstung @moritzgerstung.bsky.social · 28/11/2025

Join us: With @abigailsuwala.bsky.social we are looking for a postdoc to drive our spatial transcriptomics analysis efforts of brain tumours. If you enjoy multidisciplinary biomedical research, big data and coding, you are in the right place. karriere.klinikum.uni-heidelberg.de/index.php?ac...

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Moritz Gerstung @moritzgerstung.bsky.social · 07/10/2025

A spatial transcriptomics analysis led by my student Zaira reveals the distinct nature (gene expression, tumour cell states and local microenvironments) of radionecrosis and recurrence in glioblastoma. 👏

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Reposted by Moritz Gerstung

EMBL-EBI @ebi.embl.org · 17/09/2025

What if you could get a glimpse of the future of your health, today? Our scientists have developed a new generative AI model, trained using large-scale health records, that can estimate how human health may change over time. Watch to find out more. 🖥️🧬

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Reposted by Moritz Gerstung

Omer Ali Bayraktar @bayraktarlab.bsky.social · 16/05/2025

How does tumour heterogeneity arise? How can we predict cancer cell plasticity? In 2 new studies, we trace #glioblastoma heterogeneity to a spatial cancer cell trajectory w. multimodal cell atlassing bit.ly/4mkrWgs & predict plasticity w. snRNA/ATAC+deep learning bit.ly/3FbI6Ic 🧵

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Moritz Gerstung @moritzgerstung.bsky.social · 26/03/2025

Our experience with the multimodal seg is similar as yours- works great for many cell types or tissues, but not all. Plus there can be contaminating transcripts on top.

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Moritz Gerstung @moritzgerstung.bsky.social · 26/03/2025

Thank you! Yes, we believe segger has an edge over membrane-based segmentation because it also recognises the co-occurrence of transcripts. You can also use 10x multi-modal instead of nuclear segmentation as seggers input.

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Moritz Gerstung @moritzgerstung.bsky.social · 20/03/2025

and also myeloproliferative neoplasms. Back then, the implementation was very clunky and could only be done by R experts. ebmstate now makes the inference much easier with only a few lines of code. www.nejm.org/doi/full/10....

nejm.org

Classification and Personalized Prognosis in Myeloproliferative Neoplasms | NEJM

Myeloproliferative neoplasms, such as polycythemia vera, essential thrombocythemia, and myelofibrosis, are chronic hematologic cancers with varied progression rates. The genomic characterization of...

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Moritz Gerstung @moritzgerstung.bsky.social · 20/03/2025

This type of model predicts a patient’s journey across several mid- and endpoints and relates the progression to hundreds of variables. It was used to learn detailed prognostic models for acute myeloid leukaemia .. www.nature.com/articles/ng....

nature.com

Precision oncology for acute myeloid leukemia using a knowledge bank approach - Nature Genetics

Peter Campbell, Hartmut Döhner and colleagues present an analysis of genetic mutations and clinical information from 1,540 patients with acute myeloid leukemia, demonstrating the utility of clinical k...

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Moritz Gerstung @moritzgerstung.bsky.social · 20/03/2025

Some classical statistics today. ebmstate, an R package for multistate models with empirical Bayes covariate effect estimation. Developed by Rui Costa during his postdoc in my group. doi.org/10.32614/RJ-...

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Reposted by Moritz Gerstung

danapeer.bsky.social @danapeer.bsky.social · 20/03/2025

From great collaborations come great things. Excited to share Segger, the solution to segmentation of spatial transcriptomics (ST) data, with the @steglelab.bsky.social and @moritzgerstung.bsky.social labs, spearheaded by the great Andrew Moorman and Elyas Heidari www.biorxiv.org/content/10.1...

biorxiv.org

Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data

The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current c...

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Reposted by Moritz Gerstung

Stegle Lab @steglelab.bsky.social · 18/03/2025

1/ New preprint! 🍳 @elihei.bsky.social and our team at @embl.org , @dkfz.bsky.social, and @mskcancercenter.bsky.social built #segger - a fast, accurate cell segmentation tool for spatial transcriptomics that assigns transcripts to their cell origins! doi.org/10.1101/2025...

Message passing intuition behind the segger’s link-prediction model and the network architecture

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Moritz Gerstung @moritzgerstung.bsky.social · 18/03/2025

Also tagging Elyas Heidari @elihei.bsky.social here who led this fantastic work.

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Moritz Gerstung @moritzgerstung.bsky.social · 17/03/2025

A great thanks goes to all the other authors and contributors from the Gerstung, Stegle and Peer labs who made this work possible.

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Moritz Gerstung @moritzgerstung.bsky.social · 17/03/2025

Andrew Moorman and other members of @danapeer.bsky.social's lab helped carry out a rigorous assessment based on various 10x Xenium data sets with bespoke segmentation stainings, providing the ground truth to demonstrate segger's superior performance.

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Moritz Gerstung @moritzgerstung.bsky.social · 17/03/2025

Segger is a super fast graph neural network algorithm, which makes cell segmentation much more reliable and faster.

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Moritz Gerstung @moritzgerstung.bsky.social · 17/03/2025

Spatial transcriptomics holds great promise to understand biological tissue function, but the assignment of transcripts to cells has been a substantial bottleneck. For this reason, Elyas Heidari, a student in my lab and in @steglelab.bsky.social built segger. www.biorxiv.org/content/10.1...

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Reposted by Moritz Gerstung

Daniel MacArthur @dgmacarthur.bsky.social · 15/03/2025

New preprint! We worked with @msftresearch.bsky.social and @broadinstitute.org to see whether large language models (LLMs) can be useful to variant scientists in deciding whether genetic variants seen in a patient are responsible for their disease. tl;dr yes they can: www.biorxiv.org/content/10.1...

biorxiv.org

Evidence Aggregator: AI reasoning applied to rare disease diagnostics

Retrieving, reviewing, and synthesizing technical information can be time-consuming and challenging, particularly when requiring specialized expertise, as is the case of variant assessment for rare di...

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Moritz Gerstung @moritzgerstung.bsky.social · 20/11/2024

Amazing work. We‘re all walking laboratories for somatic evolution.

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Reposted by Moritz Gerstung

Inigo Martincorena @imartincorena.bsky.social · 20/11/2024

Resharing here a recent X post. In this preprint, we introduce an improved version of NanoSeq, a duplex sequencing protocol with <5 errors per billion bp in single DNA molecules, and use it to study the somatic mutation landscape of oral epithelium in >1000 people. 1/ www.medrxiv.org/content/10.1...

medrxiv.org

Somatic mutation and selection at epidemiological scale

As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations ([1][1]–[10][2]. Some of these clones represent a first step towards cancer whereas others may contribu...

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Moritz Gerstung @moritzgerstung.bsky.social · 20/11/2024

Safe travels! We’re still waiting for the snow you got yesterday to arrive but chances look slim. Probably better travel wise.

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Moritz Gerstung @moritzgerstung.bsky.social · 18/11/2024

Thanks. Was on a bit of a social media hiatus, but this place looks like a new hope.

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Moritz Gerstung @moritzgerstung.bsky.social · 18/11/2024

Congratulations! Looking forward to seeing the outputs of your scientific ingenuity becoming multiplied.

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Reposted by Moritz Gerstung

Altmetric @altmetric.com · 18/11/2024

We strongly suggest that academic publishers and other platforms that host research rapidly implement a Share to Bluesky button for their articles. Here's how: docs.bsky.app/docs/advance... #AcademicSky #HigherEd #Altmetrics

docs.bsky.app

Action Intent Links | Bluesky

Authors, websites, and apps can use action intent links to implement "Share on Bluesky" buttons, or similar in-app actions. Logged-in users will be directed to the corresponding action view in the Blu...

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Moritz Gerstung @moritzgerstung.bsky.social · 18/11/2024

3/3 Paion is a new algorithm to diagnose brain cancers from H&E images. * distinguishes 102 types of brain cancer * high confidence predictions in 50-70% of cases across 7 cohorts * top1 acc > 85% in high conf subset * 2 day turnaround v 3 weeks for molecular testing Preprint coming soon.

Example Paion report for a confirmed myxopapillary ependymoma diagnosis. Shown are H&E, prediction heatmaps and automatically selected representative image tiles.

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Moritz Gerstung @moritzgerstung.bsky.social · 18/11/2024

2/3 Delphi-2M generative AI model for multi-disease risks * a single GPT-derived model learns risks of 1257 diseases * samples future life courses * offers insights into multi-morbidity dynamics www.medrxiv.org/content/10.1...

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Moritz Gerstung @moritzgerstung.bsky.social · 18/11/2024

5:20 start this morning for a virtual talk at the WEHI in Melbourne, covering: * Cancer risk models * Delphi multi-disease genAI * Paion, a new brain tumor digital pathology algorithm Summary below:

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Reposted by Moritz Gerstung

Eric Topol @erictopol.bsky.social · 14/11/2024

New at Science Evo, a large language of life (LLLM) genomic foundation model, predicting & generating tasks from molecular to genomic scale science.org/doi/10.1126/...

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