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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.
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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.

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Citations
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Uncertainty-based Gompertz growth model for tumor population and its numerical analysis

TL;DR: F fuzzy tumor growth modeling insights based on fuzziness are examined to reduce tumor uncertainty and achieve a degree of realism.

A mathematical analysis of aerobic glycolysis triggered by glucose uptake in cones

TL;DR: This work develops a nonlinear system of enzymatic functions and differential equations to mathematically model molecular and cellular interactions in a cone and uses uncertainty and sensitivity analysis to identify processes that have the largest effect on the system and their timeframes.
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Dynamics of a seasonal brucellosis disease model with nonlocal transmission and spatial diffusion

TL;DR: It is suggested that herdsmen should improve the sanitation of animals’ environment and isolate infected animals instantly to control brucellosis prevalence and elucidate that time heterogeneity enhances magnitudes of oscillations of animal population and brucella.
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Origin of tuberculosis in the Paleolithic predicts unprecedented population growth and female resistance

TL;DR: A higher resistance/tolerance to females is attributed to explain the lower incidence noted in this sex, a better health status in the Paleolithic compared to the Neolithic, and a higher dissemination of “modern” lineages compared to “ancient” ones.
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Response Acceleration in Post-translationally Regulated Genetic Circuits

TL;DR: The authors' mathematical modeling demonstrates that sensor-targeting mechanisms exhibit stronger response acceleration than those where the connector targets the regulator, and the relationship between the architecture of genetic regulatory circuits and their dynamic properties is highlighted.
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

Max D. Morris
- 01 Jan 1992 - 
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.
Journal ArticleDOI

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.
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