A Methodology For Performing Global Uncertainty And Sensitivity Analysis In Systems Biology
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TLDR
This work develops methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models and provides a complete methodology for performing these analyses, in both deterministic and stochastic settings, and proposes novel techniques to handle problems encountered during these types of analyses.About:
This article is published in Journal of Theoretical Biology.The article was published on 2008-09-07 and is currently open access. It has received 2014 citations till now. The article focuses on the topics: Uncertainty analysis & Sensitivity analysis.read more
Citations
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Parameter Trajectory Analysis to Identify Treatment Effects of Pharmacological Interventions
CA Christian Tiemann,CA Christian Tiemann,J Joep Vanlier,J Joep Vanlier,Maaike H. Oosterveer,Albert K. Groen,Albert K. Groen,Peter A. J. Hilbers,Peter A. J. Hilbers,Natal A. W. van Riel,Natal A. W. van Riel +10 more
TL;DR: It is demonstrated how ADAPT can be used to design new target interventions to prevent potential unwanted side effects, and provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1), a receptor that facilitates the hepatic uptake of cholesterol.
Journal ArticleDOI
A multi-scale approach to designing therapeutics for tuberculosis
TL;DR: An in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis is presented.
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Optimizing the deployment of ultra-low volume and targeted indoor residual spraying for dengue outbreak response.
Sean M. Cavany,Guido España,Alun L. Lloyd,Lance A. Waller,Uriel Kitron,Helvio Astete,William H. Elson,Gonzalo M. Vazquez-Prokopec,Thomas W. Scott,Amy C. Morrison,Robert C. Reiner,T. Alex Perkins +11 more
TL;DR: Although spraying twice each year is likely to avert the most infections, the results indicate that a threshold-based strategy can become an alternative to better balance the translation of spraying effort into impact, particularly if used with a residual insecticide.
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Optimal control and cost-effective analysis of the 2017 meningitis outbreak in Nigeria.
TL;DR: Optimal control theory was applied to investigate the optimal strategy for curtailing the spread of the disease using control variables determined from sensitivity analysis and strategy combining all the control variables is the most cost-effective strategy followed by the strategy involving both personal-protection and vaccination.
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Persistent oscillations and backward bifurcation in a malaria model with varying human and mosquito populations: implications for control
TL;DR: Malaria dynamics are indeed oscillatory when the methodology of explicitly incorporating the mosquito’s demography, feeding and reproductive patterns is considered in modeling the mosquito population dynamics, and uncertainties in the estimations of the rates at which exposed humans become infectious and infectious humans recover from malaria are critical in generating uncertainties.
References
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Book
An Introduction to Multivariate Statistical Analysis
TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
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A comparison of three methods for selecting values of input variables in the analysis of output from a computer code
TL;DR: In this paper, two sampling plans are examined as alternatives to simple random sampling in Monte Carlo studies and they are shown to be improvements over simple sampling with respect to variance for a class of estimators which includes the sample mean and the empirical distribution function.
Journal Article
Factorial sampling plans for preliminary computational experiments
TL;DR: The proposed experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects, those changes in an output due solely to changes in a particular input.
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Factorial sampling plans for preliminary computational experiments
TL;DR: In this article, the problem of designing computational experiments to determine which inputs have important effects on an output is considered, and experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects.