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This work introduces a novel, scalable branched flow-matching algorithm designed to solve the branched optimal transport problem in high dimensions and demonstrates its effectiveness on challenging high-dimensional tasks in biology and image generation.
EpiBinder is presented, a multimodal deep-learning framework for cell-type-specific prediction of TF binding that jointly models DNA sequence with base-resolution epigenetic information, including cytosine methylation from whole-genome bisulfite sequencing and chromatin accessibility from DNase I hypersensitivity data.
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