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Mimyr: Generative modeling of missing tissue in spatial transcriptomics

Preprint on bioRxiv, 2025

Mimyr is a generative framework for reconstructing missing regions and virtual slices in spatial transcriptomics data caused by tissue damage or incomplete sampling. It jointly predicts cell locations, cell types, and gene expression profiles using a three-staged pipeline. Mimyr produces realistic, high-fidelity reconstructions across experimental settings and outperforms existing methods in both accuracy, efficiency and robustness.

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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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