Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions

Abstract Existing computational methods that use single-cell RNA-sequencing (scRNA-seq) for cell fate prediction do not model how cells evolve stochastically and in physical time, nor can they predict how differentiation trajectories are altered by proposed interventions. We introduce PRESCIENT (Po...

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Bibliographic Details
Main Authors: Yeo, Grace Hui Ting, Saksena, Sachit D, Gifford, David K
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2022
Online Access:https://hdl.handle.net/1721.1/143571