A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases.
Europe PMC REST API · Indexed academic record · Source published: Fri Jun 20 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:08:13 GMT+0000 (Coordinated Universal Time)
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Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures
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