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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Identifying mechanisms driving formation of granuloma-associated fibrosis during Mycobacterium tuberculosis infection
Hayley Warsinske,Robert M. DiFazio,Jennifer J. Linderman,JoAnne L. Flynn,Denise E. Kirschner +4 more
TL;DR: It is suggested that heterogeneous cytokine environments exist within granulomas and may be responsible for driving tissue scale morphologies, a necessity for developing successful treatments for TB.
Journal ArticleDOI
Modeling the role of fomites in a norovirus outbreak.
Robert A. Canales,Kelly A. Reynolds,Amanda M. Wilson,Sonia L.M. Fankem,Mark H. Weir,Joan B. Rose,Sherif Abd-Elmaksoud,Charles P. Gerba +7 more
TL;DR: This model suggests that fomites may have accounted for 25% to 82% of illnesses in this outbreak of norovirus, and reinforces the importance of frequent fomite cleaning and hand washing, especially when ill persons are present.
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A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks
TL;DR: A systems biology approach combining data-driven modeling and model-driven experiments is presented to investigate mechanisms of collective repression on p21 by multiple miRNAs to study the effect of different miRNA expression profiles and cooperative target regulation on p 21 expression levels in different biological contexts.
Journal ArticleDOI
The dual role of dendritic cells in the immune response to human immunodeficiency virus type 1 infection.
Ian B. Hogue,Seema H. Bajaria,Beth A. Fallert,Shulin Qin,Todd A. Reinhart,Denise E. Kirschner +5 more
TL;DR: A mathematical model describing the dynamics of HIV-1, CD4+ and CD8+ T-cells, and DCs interacting in a human lymph node was analysed and is presented here and predicted that simultaneous priming and infection of T cells by DCs drives early infection dynamics when activated T-helper cell numbers are low.
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Sorafenib metabolism, transport, and enterohepatic recycling: physiologically based modeling and simulation in mice
Andrea N. Edginton,Eric I. Zimmerman,Aksana Vasilyeva,Sharyn D. Baker,Sharyn D. Baker,John C. Panetta +5 more
TL;DR: Translation of the mouse model to humans for the purpose of explaining exceptionally high human pharmacokinetic variability and its relationship with exposure-dependent dose-limiting toxicities will require delineation of the importance of these processes on disposition.
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.