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Bayesian Parameter Estimation for Stochastic Reaction Networks from Steady-State Observations
- Source :
- Computational Methods in Systems Biology ISBN: 9783030313036, CMSB
- Publication Year :
- 2019
- Publisher :
- Springer International Publishing, 2019.
-
Abstract
- Stochasticity is a fundamental feature of biology at the single cell level. Quantitative experimental data ranging from microscopy to single-cell transcriptomic is continually expanding our understanding of the role of stochasticity in gene expression and other cellular processes.
- Subjects :
- 050101 languages & linguistics
Steady state (electronics)
Feature (computer vision)
05 social sciences
0202 electrical engineering, electronic engineering, information engineering
Experimental data
020201 artificial intelligence & image processing
0501 psychology and cognitive sciences
Ranging
02 engineering and technology
Cellular level
Biological system
Bayesian parameter estimation
Subjects
Details
- ISBN :
- 978-3-030-31303-6
- ISBNs :
- 9783030313036
- Database :
- OpenAIRE
- Journal :
- Computational Methods in Systems Biology ISBN: 9783030313036, CMSB
- Accession number :
- edsair.doi...........05ed59d73c1ea5ed13cfe1ee856808c0
- Full Text :
- https://doi.org/10.1007/978-3-030-31304-3_23