Cargando…
A Computational Framework for Analyzing Stochasticity in Gene Expression
Stochastic fluctuations in gene expression give rise to distributions of protein levels across cell populations. Despite a mounting number of theoretical models explaining stochasticity in protein expression, we lack a robust, efficient, assumption-free approach for inferring the molecular mechanism...
Autores principales: | Sherman, Marc S., Cohen, Barak A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4014403/ https://www.ncbi.nlm.nih.gov/pubmed/24811315 http://dx.doi.org/10.1371/journal.pcbi.1003596 |
Ejemplares similares
-
Analyzing stochastic transcription to elucidate the nucleoid's organization
por: Riva, Alessandra, et al.
Publicado: (2008) -
A Scalable Computational Framework for Establishing Long-Term Behavior of Stochastic Reaction Networks
por: Gupta, Ankit, et al.
Publicado: (2014) -
Development of a theoretical framework for analyzing cerebrospinal fluid dynamics
por: Cohen, Benjamin, et al.
Publicado: (2009) -
Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework
por: Zhang, Siliang, et al.
Publicado: (2022) -
Stochastic Gene Expression Revisited
por: Tomski, Andrzej, et al.
Publicado: (2021)