Using deep learning to quantify neuronal activation from single-cell and spatial transcriptomic data

Abstract Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activ...

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Hlavní autoři:	Ethan Bahl, Snehajyoti Chatterjee, Utsav Mukherjee, Muhammad Elsadany, Yann Vanrobaeys, Li-Chun Lin, Miriam McDonough, Jon Resch, K. Peter Giese, Ted Abel, Jacob J. Michaelson
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2024-01-01
Edice:	Nature Communications
On-line přístup:	https://doi.org/10.1038/s41467-023-44503-5
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