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Article

Machine learning-predicted chromatin organization landscape across pediatric tumors

2025-04-02

Abstract excerpt

Structural variants (SVs) are increasingly recognized as important contributors to oncogenesis through their effects on 3D genome folding. Recent advances in whole-genome sequencing have enabled large-scale profiling of SVs across diverse tumors, yet experimental characterization of their individual impact on genome folding remains infeasible. Here, we leveraged a convolutional neural network, Akita, to predict di...

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Identifiers and source

Literature Corpus work
41278d38-6c86-584b-a54c-37e170d19af9
DOI
10.1101/2025.03.28.645984
Open publication

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Machine learning-predicted chromatin organization landscape across pediatric tumorsDOI 10.1101/2025.03.28.645984
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