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RESEARCH ARTICLE Open Access Thermodynamic modeling of transcription
 

Summary: RESEARCH ARTICLE Open Access
Thermodynamic modeling of transcription:
sensitivity analysis differentiates biological
mechanism from mathematical model-induced
effects
Jacqueline M Dresch1
, Xiaozhou Liu2
, David N Arnosti2*
, Ahmet Ay3,4*
Abstract
Background: Quantitative models of gene expression generate parameter values that can shed light on biological
features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in
such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in
parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted
conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model
structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze
gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has
been given to parameter sensitivity in this context.
Results: We apply local and global sensitivity analyses to two recent transcriptional models to determine the
sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive,

  

Source: Arnosti, David N. - Department of Biochemistry and Molecular Biology, Michigan State University

 

Collections: Biology and Medicine