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Elizabeth Scribner
Researcher at University of Alabama at Birmingham
Publications - 7
Citations - 106
Elizabeth Scribner is an academic researcher from University of Alabama at Birmingham. The author has contributed to research in topics: Glioma & Estimation theory. The author has an hindex of 5, co-authored 7 publications receiving 98 citations. Previous affiliations of Elizabeth Scribner include University of Alabama.
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Journal ArticleDOI
Effects of Anti-Angiogenesis on Glioblastoma Growth and Migration: Model to Clinical Predictions
Elizabeth Scribner,Olivier Saut,Paula Province,Asim K. Bag,Thierry Colin,Hassan M. Fathallah-Shaykh +5 more
TL;DR: A clinical-scale model of GBM is constructed whose predictions uncover a new pattern of recurrence in 11/70 bevacizumab-treated patients and support an exception to the Folkman hypothesis: GBM grows in the absence of angiogenesis by a cycle of proliferation and brain invasion that expands necrosis.
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Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme
Fabio Raman,Elizabeth Scribner,Olivier Saut,Cornelia Wenger,Thierry Colin,Hassan M. Fathallah-Shaykh +5 more
TL;DR: A mathematical model of glioblastoma multiforme growth and invasion in humans and computational trials using agents that target angiogenesis, tumor replication rates, or motility are applied and a correlation was observed between the efficacy of the rate-reducing agent and the prolongation of overall survival times.
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Single Cell Mathematical Model Successfully Replicates Key Features of GBM: Go-Or-Grow Is Not Necessary.
TL;DR: It is suggested that the GoG phenotype is not a necessary property for the formation of the multilayer structure, recurrence patterns, and the poor survival times of patients diagnosed with GBM.
Journal ArticleDOI
Proper orthogonal decomposition for parameter estimation in oscillating biological networks
TL;DR: The findings reveal that POD generates accurate estimates of the parameters even in the presence of experimental noise; furthermore, extrapolating biologically measured data points to a number of oscillations improves the curve fits, C^1 approximations, and parameter estimations.
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Key rates for the grades and transformation ability of glioma: model simulations and clinical cases.
Elizabeth Scribner,James R. Hackney,Hannah C. Machemehl,Reina Afiouni,Krishna R. Patel,Hassan M. Fathallah-Shaykh,Hassan M. Fathallah-Shaykh +6 more
TL;DR: The hypothesis that constant rates of dispersion, proliferation, and angiogenesis prescribe either a natural evolution or the inability to progress to higher grades is supported.