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 (Pot...
Main Authors: | Yeo, Grace Hui Ting (Author), Saksena, Sachit D (Author), Gifford, David K (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer Science and Business Media LLC,
2022-06-28T13:36:55Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions
by: Grace Hui Ting Yeo, et al.
Published: (2021-05-01) -
Fragmented Self: Hawthorne’s Prescient Eye in “The Prophetic Pictures” and “Wakefield”
by: Naruhiko Mikado
Published: (2019-07-01) -
Once upon a market dreary: the prescient marketing principles of Edgar Allan Poe
by: Brown, S., et al.
Published: (2018) -
Tempora: Cell trajectory inference using time-series single-cell RNA sequencing data.
by: Thinh N Tran, et al.
Published: (2020-09-01) -
Expansion microscopy: enabling single cell analysis in intact biological systems
by: Alon, Shahar, et al.
Published: (2020)