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 · 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 · 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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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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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

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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