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
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Optimizing insecticide allocation strategies based on houses and livestock shelters for visceral leishmaniasis control in Bihar, India
TL;DR: A novel optimization model is developed and analyzed for VL control in Bihar that identifies an optimal (best possible) allocation of chosen insecticide (dichlorodiphenyltrichloroethane [DDT] or deltamethrin) based on the sizes of human and cattle populations in the region.
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Strategic Priming with Multiple Antigens can Yield Memory Cell Phenotypes Optimized for Infection with Mycobacterium tuberculosis: A Computational Study.
TL;DR: It is hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population, and a computational model is created to explore EM andCM values, and their ratio, within what is term Memory Design Space.
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Early antiretroviral therapy and potent second-line drugs could decrease HIV incidence of drug resistance.
Mingwang Shen,Mingwang Shen,Yanni Xiao,Libin Rong,Libin Rong,Lauren Ancel Meyers,Lauren Ancel Meyers,Steven E. Bellan +7 more
TL;DR: An infection-age-structured mathematical model was constructed that tracked the transmission rates over the course of infection and modelled the patients' life expectancy as a function of ART initiation timing and found that resistance may paradoxically appear to be increasing while actually decreasing.
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Computational modeling of synergistic interaction between αVβ3 integrin and VEGFR2 in endothelial cells: Implications for the mechanism of action of angiogenesis-modulating integrin-binding peptides.
TL;DR: A rule-based computational model was developed to investigate the potential mechanism by which the Src-induced integrin association with V EGFR2 enhances VEGFR2 activation and proposed potential molecular mechanisms for the angiogenesis-modulating activity of other integrin-binding peptides.
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Assessing the potential impact of Salmonella vaccines in an endemically infected dairy herd.
TL;DR: A deterministic compartmental model with both replacement (cohort) and lifetime (continuous) vaccination strategies was developed and applied to a Salmonella Cerro infection in a dairy farm, and results show that imperfectSalmonella vaccines reduce the prevalence of Salmoneella Cerro.
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.