Article

MIMYR: Generative modeling of missing tissue in spatial transcriptomics

2025-11-27

Abstract excerpt

Spatial transcriptomics enables the study of how gene expression is organized across tissues, revealing how cells interact within their native microenvironments in health and disease. However, tissue damage during sectioning and the allocation of intermediate slices to other assays often result in regions or entire planes missing from the data, limiting downstream analysis. Here, we introduce MIMYR, a generative f...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1f275e01-70c3-57a5-a2a9-8fcd9aad4488
DOI: 10.1101/2025.11.24.690239

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

MIMYR: Generative modeling of missing tissue in spatial transcriptomicsDOI 10.1101/2025.11.24.690239Read

scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial TranscriptomicsSemantic proximity Read

Construction of a 3D whole organism spatial atlas by joint modeling of multiple slicesSemantic proximity Read

INSPIRE: interpretable, flexible and spatially-aware integration of multiple spatial transcriptomics datasets from diverse sourcesSemantic proximity Read

Tissue Reassembly with Generative AISemantic proximity Read

STODE: A Deep Generative Framework for Continuous Spatiotemporal Dynamics in Spatial TranscriptomicsSemantic proximity Read

UniST: A Unified Computational Framework for 3D Spatial Transcriptomics ReconstructionSemantic proximity Read

Three-dimensional spatial transcriptomics at isotropic resolution enabled by generative deep learningSemantic proximity Read

Inferring single-cell spatial gene expression with tissue morphology via explainable deep learningSemantic proximity Read

Ultra-efficient High Resolution 3D Reconstruction of Spatial Omics Data with Neural Transcriptomic FieldSemantic proximity Read

LYNX: a deep generative model for linking spatial dynamics and cell interactions in multimodal spatial dataSemantic proximity Read

Statistical batch-aware embedded integration, dimension reduction and alignment for spatial transcriptomicsSemantic proximity Read

Enhancing Pan-cancer Spatial Transcriptomics at Single-cell Resolution with STPAINTERSemantic proximity Read