Filter inference: a scalable nonlinear mixed effects inference approach for snapshot time series data
Variability is an intrinsic property of biological systems and is often at the heart of their complex behaviour. Examples range from cell-to-cell variability in cell signalling pathways to variability in the response to treatment across patients. A popular approach to model and understand this varia...
Huvudupphovsmän: | Augustin, D, Lambert, B, Wang, K, Walz, A-C, Robinson, M, Gavaghan, D |
---|---|
Materialtyp: | Journal article |
Språk: | English |
Publicerad: |
Public Library of Science
2023
|
Liknande verk
-
Bayesian time series models and scalable inference
av: Johnson, Matthew James, Ph. D. Massachusetts Institute of Technology
Publicerad: (2014) -
Probabilistic inference on noisy time series (PINTS)
av: Clerx, M, et al.
Publicerad: (2019) -
Scalable online nonlinear goal-oriented inference with physics-informed maps
av: Li, Harriet.
Publicerad: (2019) -
Scalable inference in state-space models
av: Middleton, L
Publicerad: (2019) -
Bayesian inference for biological time series
av: Creswell, R
Publicerad: (2023)