Validation methods for population models of gene expression dynamics
The advent of experimental techniques for the time-course monitoring of gene expression at the single-cell level has paved the way to the model-based study of gene expression variability within- an across-cells. A number of approaches to the inference of models accounting for variability of gene exp...
- Autores:
-
González Vargas, Andrés Mauricio
Cinquemani, Eugenio
Ferrari Trecate, Giancarlo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2016
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/11041
- Palabra clave:
- Statistical methods
System biology
Stochastic modelling
Mixed-effects modelling
Gene expression
Expresión del gen
Modelos biológicos
Biological models
- Rights
- openAccess
- License
- Derechos Reservados - Universidad Autónoma de Occidente
| Summary: | The advent of experimental techniques for the time-course monitoring of gene expression at the single-cell level has paved the way to the model-based study of gene expression variability within- an across-cells. A number of approaches to the inference of models accounting for variability of gene expression over isogenic cell populations have been developed and applied to real-world scenarios. The development of a systematic approach for the validation of population models is however lagging behind, and accuracy of the models obtained is often assessed on a semi-empirical basis. In this paper we study the problem of validating models of gene network dynamics for cell populations, providing statistical tools for qualitative and quantitative model validation and comparison, and guidelines for their application and interpretation based on a real biological case study |
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