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Modeling metastatic progression from cross-sectional cancer genomics data

URN to cite this document:
urn:nbn:de:bvb:355-epub-584734
Rupp, Kevin ; Lösch, Andreas ; Hu, Y. Linda ; Nie, Chenxi ; Schill, Rudolf ; Klever, Maren ; Pfahler, Simon ; Grasedyck, Lars ; Wettig, Tilo ; Beerenwinkel, Niko ; Spang, Rainer
[img]License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 23 Jul 2024 05:52



Abstract

Motivation Metastasis formation is a hallmark of cancer lethality. Yet, metastases are generally unobservable during their early stages of dissemination and spread to distant organs. Genomic datasets of matched primary tumors and metastases may offer insights into the underpinnings and the dynamics of metastasis formation. Results We present metMHN, a cancer progression model designed to ...

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