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Decoding and steering spatially resolved cellular dynamics
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DOI：10.1038/s44320-026-00216-7.png)
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Abstract
En 中文
Understanding how cells transition between states is central to biology. RNA velocity has emerged as a transformative framework for inferring future cellular states from unspliced and spliced mRNA transcripts. A new deep generative and agent‑based method can decode and manipulate cellular dynamics within native tissue by dissecting spatially resolved RNA velocity and simulating regulatory interventions, opening new opportunities to explore how tissue context shapes and potentially controls cell‑state transitions. This News &Views highlights a recent study by Raghavan and colleagues (in this issue of MSB) that introduces veloAgent, a computational framework that integrates transcriptional dynamics with spatial information to dissect spatially resolved RNA velocity.
Keywords:
RNA velocity
cellular dynamics
spatial transcriptomics
computational modeling
cell-state transitions
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