Cargando…
Optimal Experimental Design Based on Two-Dimensional Likelihood Profiles
Dynamic behavior of biological systems is commonly represented by non-linear models such as ordinary differential equations. A frequently encountered task in such systems is the estimation of model parameters based on measurement of biochemical compounds. Non-linear models require special techniques...
Autores principales: | Litwin, Tim, Timmer, Jens, Kreutz, Clemens |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906444/ https://www.ncbi.nlm.nih.gov/pubmed/35281278 http://dx.doi.org/10.3389/fmolb.2022.800856 |
Ejemplares similares
-
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
por: Kreutz, Clemens, et al.
Publicado: (2012) -
‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’
por: Mehmood, Sabba, et al.
Publicado: (2022) -
Driving the Model to Its Limit: Profile Likelihood Based Model Reduction
por: Maiwald, Tim, et al.
Publicado: (2016) -
The performance of deep generative models for learning joint embeddings of single-cell multi-omics data
por: Brombacher, Eva, et al.
Publicado: (2022) -
Two-dimensional measurements of receptor-ligand interactions
por: Zheng, Songjie, et al.
Publicado: (2023)