ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2008
A new strategy for assessing sensitivities in biochemical models.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Computational Modeling Reveals Frequency Modulation of Calcium-cAMP/PKA Pathway in Dendritic Spines.Biophysical journal · 2019Article
- Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2017Article
- Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models.CPT: pharmacometrics & systems pharmacology · 2015Article
- Global sensitivity analysis of a mathematical model of acute inflammation identifies nonlinear dependence of cumulative tissue damage on host interleukin-6 responses.Journal of theoretical biology · 2014Article
- Model of tryptophan metabolism, readily scalable using tissue-specific gene expression data.The Journal of biological chemistry · 2013Article
- Approaches and tools for modeling signaling pathways and calcium dynamics in neurons.Journal of neuroscience methods · 2013Review
- Prediction stability in a data-based, mechanistic model of σF regulation during sporulation in Bacillus subtilis.Scientific reports · 2013Article
- A computational model of liver iron metabolism.PLoS computational biology · 2013Article
- Article
- Condor-COPASI: high-throughput computing for biochemical networks.BMC systems biology · 2012Article
- Biochemical fluctuations, optimisation and the linear noise approximation.BMC systems biology · 2012Article
- Identification of Critical Molecular Components in a Multiscale Cancer Model Based on the Integration of Monte Carlo, Resampling, and ANOVA.Frontiers in physiology · 2011Article
- Towards a unifying, systems biology understanding of large-scale cellular death and destruction caused by poorly liganded iron: Parkinson's, Huntington's, Alzheimer's, prions, bactericides, chemical toxicology and others as examples.Archives of toxicology · 2010Review
- A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis.BMC systems biology · 2009Article
- Molecular mechanisms underlying neuronal synaptic plasticity: systems biology meets computational neuroscience in the wilds of synaptic plasticity.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
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Authors and funding
4 authors.
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Abstract
An integral part of any systems biology approach is the modelling and simulation of the respective system under investigation. However, the values of many parameters of the system have often not been determined or are not identifiable due to technical experimental difficulties or other constraints. Sensitivity analysis is often employed to quantify the importance of each of the model's parameters in the behaviour of the system. This approach can also be useful in identifying those parts of the system that are most sensitive with the potential of becoming drug targets. A problem of the commonly used methods of sensitivity analysis is that they constitute local methods meaning that they depend directly on the exact parameter space, which in turn is not known exactly. One way to circumvent this problem is to carry out sensitivity analysis over a wide range of values for all parameters, but this is handicapped by expensive computations when the systems are high dimensional. Another approach is to employ global sensitivity analysis, which in this context is mostly based on random sampling methods. In this paper we present an efficient approach that involves using numerical optimizing methods that search a wide region of parameter space for a given model to determine the maximum and minimum values of its metabolic control coefficients. A relevant example for drug development is presented to demonstrate the strategy using the software COPASI.
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