Randomization and Monte Carlo Methods in Biology

Manly, Bryan F. J.

doi:10.1007/978-1-4899-2995-2

Cited by 1,922 publications

(1,882 citation statements)

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“…The permutational p-values for the difference between paired samples were calculated using a webbased program written in CGI/PERL and is available for use at http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/BonnieLaFleur. These paired permutation tests use algorithms developed by Fisher [12], and described in detail in a paper by Manly [24]. Permutation tests for paired samples are similar to their parametric counterpart (the paired t-test) in that the test statistic is based on the difference between the two correlated samples (in this case NFT and non-NFT samples on the same individuals).…”

Section: Discussionmentioning

confidence: 99%

Gene expression correlates of neurofibrillary tangles in Alzheimer's disease

Dunckley

Beach²,

Ramsey

et al. 2006

Neurobiology of Aging

159

134

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Neurofibrillary tangles (NFT) constitute one of the cardinal histopathological features of Alzheimer's disease (AD). To explore in vivo molecular processes involved in the development of NFTs, we compared gene expression profiles of NFT-bearing entorhinal cortex neurons from 19 AD patients, adjacent non-NFT-bearing entorhinal cortex neurons from the same patients, and non-NFT-bearing entorhinal cortex neurons from 14 non-demented, histopathologically normal controls (ND). Of the differentially expressed genes, 225 showed progressively increased expression (AD NFT neurons > AD non-NFT neurons > ND non-NFT neurons) or progressively decreased expression (AD NFT neurons < AD non-NFT neurons < ND non-NFT neurons), raising the possibility that they may be related to the early stages of NFT formation. Immunohistochemical studies confirmed that many of the implicated proteins are dysregulated and preferentially localized to NFTs, including apolipoprotein J, interleukin-1 receptor-associated kinase 1, tissue inhibitor of metalloproteinase 3, and casein kinase 2, beta. Functional validation studies are underway to determine which candidate genes may be causally related to NFT neuropathology, thus providing therapeutic targets for the treatment of AD.

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Section: Discussionmentioning

confidence: 99%

Gene expression correlates of neurofibrillary tangles in Alzheimer's disease

Dunckley

Beach²,

Ramsey

et al. 2006

Neurobiology of Aging

159

134

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“…We applied permutation tests suggested by Manly (2006) to compare the thresholds a 1 and a 2 and the second slopes b 21 and b 22 for each of the three age groups and brain regions. We used this method because the placebo-infused fetuses at 60% of gestation, preterm, and newborn lambs provided the basal 'control' values both in the current study (Figures 1-3, open circles) and our former work (Stonestreet et al, 2006).…”

Section: Comparison Of K I Versus Plasma Osmolality Model Parameters mentioning

confidence: 99%

Comparative Effects of Glucose- and Mannitol-Induced Osmolar Stress on Blood—Brain Barrier Function in Ovine Fetuses and Lambs

Stonestreet

Sadowska

Hanumara

et al. 2011

J Cereb Blood Flow Metab

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We examined the effects of hyperglycemic hyperosmolality on blood-brain barrier (BBB) permeability during development. We hypothesized that the barrier becomes more resistant to hyperglycemic hyperosmolality during development, and the immature BBB is more resistant to glucose than to mannitol hyperosmolality. We quantified the BBB response to hyperosmolality with the blood-to-brain transfer constant (K i ) in immature fetuses, premature, and newborn lambs. K i increased as a function of increases in osmolality. A segmented regression model described the relationship between K i and osmolality. At lower osmolalities, changes in K i were minimal but after a threshold, increases were linear. We examined responses of K i to hyperglycemic hyperosmolality by comparing the thresholds and slopes of the second regression segments. Lower thresholds and steeper slopes indicate greater vulnerability to hyperosmolality. Thresholds increased (P < 0.05) during development in pons and superior colliculus. Thresholds were higher (P < 0.05) during glucose than mannitol hyperosmolality in thalamus, superior colliculus, inferior colliculus and medulla of premature lambs, and in cerebrum and cerebellum of newborns. We conclude that BBB permeability increased as a function of changes in glucose osmolality, the barrier becomes more resistant to glucose hyperosmolality in two brain regions during development, and the barrier is more resistant to glucose than to mannitol hyperosmolality in some brain regions of premature and newborn lambs.

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“…This can be assessed rigorously by using a permutation test (Manly, 1997). At each position i ∈ {1, N F }, we can compute the mean Kolomogorov-Smirnov distance between the distribution of F at the position i and the distribution of F in the neighboring cells.…”

Section: Results Posterior Distribution Of the Fitness Parameter Fmentioning

confidence: 99%

A statistical-reaction–diffusion approach for analyzing expansion processes

Roques

Soubeyrand²,

Rousselet³

2011

Journal of Theoretical Biology

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In this article, we propose a method for analyzing the spatial variations in the range expansion of the pine processionary moth (PPM), an invasive species in France. Based on binary measurements -the presence or absence of PPM nests -the proposed method allows us to infer the local effect of the environment on PPM population expansion. This effect is estimated at each position x using a parameter F (x) that corresponds to the local PPM fitness. The data type and the two stage PPM life cycle make estimating this parameter difficult. To overcome these difficulties we adopt a mechanistic-statistical approach that combines a statistical model for the observation process with a hierarchical, reaction-diffusion based mechanistic model for the expansion process. Bayesian inference of the parameter F (x) reveals that PPM fitness is spatially heterogeneous and highlights the existence of large regions associated with lower fitness. The factors underlying this lower fitness are yet to be determined.

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Randomization and Monte Carlo Methods in Biology

Cited by 1,922 publications

References 0 publications

Gene expression correlates of neurofibrillary tangles in Alzheimer's disease

Gene expression correlates of neurofibrillary tangles in Alzheimer's disease

Comparative Effects of Glucose- and Mannitol-Induced Osmolar Stress on Blood—Brain Barrier Function in Ovine Fetuses and Lambs

A statistical-reaction–diffusion approach for analyzing expansion processes

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