arXiv Machine Learning August 18, 2026 By Mary Chriselda Antony Oliver, Kaitlyn Hohmeier, Tuyen Tran, Alejandra Castillo, Caroline Moosm\"uller, Shiying Li

A Unified Geometric Framework for Developmental Analysis of Spatial Transcriptomic Data

Read the original on arXiv Machine Learning →

arXiv:2608. 15306v1 Announce Type: cross Abstract: High-throughput single-cell and spatial transcriptomic technologies provide high-resolution snapshots of heterogeneous cellular states, but their destructive nature prevents repeated measurements of the same cells over time.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data

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