Moritz Gerstung
@moritzgerstung.bsky.social
Scientist developing AI for oncology. Division head at the German Cancer Research Centre DKFZ. Prof at the University of Heidelberg, Germany. Previously at EMBL-EBI and Wellcome Sanger Institute. Alumnus of ETH Zurich.
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.
Plus there can be contaminating transcripts on top.
March 26, 2025 at 7:47 PM
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.
Plus there can be contaminating transcripts on top.
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.
March 26, 2025 at 7:45 PM
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.
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....
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....
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...
www.nejm.org
March 20, 2025 at 2:03 PM
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....
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....
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....
It was used to learn detailed prognostic models for acute myeloid leukaemia ..
www.nature.com/articles/ng....
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...
www.nature.com
March 20, 2025 at 2:03 PM
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....
It was used to learn detailed prognostic models for acute myeloid leukaemia ..
www.nature.com/articles/ng....
Also tagging Elyas Heidari @elihei.bsky.social here who led this fantastic work.
March 18, 2025 at 10:22 AM
Also tagging Elyas Heidari @elihei.bsky.social here who led this fantastic work.
A great thanks goes to all the other authors and contributors from the Gerstung, Stegle and Peer labs who made this work possible.
March 17, 2025 at 4:19 PM
A great thanks goes to all the other authors and contributors from the Gerstung, Stegle and Peer labs who made this work possible.
Segger comes as robust open-source software and has already been tested by many in the community. github.com/EliHei2/segg...
GitHub - EliHei2/segger_dev: a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting indiv...
a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex ima...
github.com
March 17, 2025 at 4:19 PM
Segger comes as robust open-source software and has already been tested by many in the community. github.com/EliHei2/segg...
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.
March 17, 2025 at 4:19 PM
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.
Segger is a super fast graph neural network algorithm, which makes cell segmentation much more reliable and faster.
March 17, 2025 at 4:19 PM
Segger is a super fast graph neural network algorithm, which makes cell segmentation much more reliable and faster.
Amazing work. We‘re all walking laboratories for somatic evolution.
November 20, 2024 at 7:25 PM
Amazing work. We‘re all walking laboratories for somatic evolution.
Safe travels! We’re still waiting for the snow you got yesterday to arrive but chances look slim. Probably better travel wise.
November 20, 2024 at 6:09 AM
Safe travels! We’re still waiting for the snow you got yesterday to arrive but chances look slim. Probably better travel wise.
Thanks. Was on a bit of a social media hiatus, but this place looks like a new hope.
November 18, 2024 at 5:20 PM
Thanks. Was on a bit of a social media hiatus, but this place looks like a new hope.