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    Potential Scenario
    167

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    2016-Wilkie-EtAl-Using ODEs to Explore Cancer-Immune Dynamics and Tumor Dormancy
    Here we present a general method using ordinary differential equations (ODEs) to model and analyze cancer-immune interactions, and in particular, immune-induced tumor dormancy.
    cancertumor-inhibiting cytotoxic actiontumor-promoting inflammationimmune-induced tumor dormancytumor growth dynamics
    Potential Scenario
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    2014-Enderling-Chaplain-Mathematical Modeling of Tumor Growth and Treatment
    Herein we describe fundamentals of mathematical modeling of tumor growth and tumor-host interactions, and summarize some of the seminal and most prominent approaches.
    cancertumor modelingangiogenesistumor growthpatient care
    Potential Scenario
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    2015-Beier-EtAl-Building Context with Tumor Growth Modeling Projects in Differential Equations
    Here we present two projects related to tumor growth appropriate for a first course in differential equations. They illustrate the use of problem-based learning to reinforce and extend course content via a writing or research experience.
    tummor growthresearch experience
    Potential Scenario
    233

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    2011-Radouane_Yafia-A Study of Differential Equations Modeling Malignant Tumor Cells in Competition with Immune System
    In this paper, we present a competition model of malignant tumor growth that includes the immune system response. The model considers two populations: immune system (effector cells) and population of tumor (tumor cells).
    Immunologytumorhopf bifrucation
    Potential Scenario
    132

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    2015-Khan-EtAl-How differential equations influence the tumor growth via mathematical models
    This work demonstrates the importance of differential equations to develop mathematical model of tumor growth.
    tumorcancdercancerous cellsimmunotherapymalignant
    Potential Scenario
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    2012-José_Sérgio_Domingues-Gompertz Model - Resolution and Analysis for Tumors
    The main objective of this paper is to use the Gompertz equation in order to study the development of blood irrigated solid tumors, using parameters defined in some important bibliographic references about the mathematical modelling of tumors.
    tumorGompertz equationgrowth tumor
    Article or Presentation
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    2015-European_Bioinformatics_Institute-Bio-Models-Database
    Bio Models Database is a repository of computational models of biological processes. Models described from literature are manually curated and enriched with cross-references. All models are provided in the Public Domain.
    biologydatabasebioinformaticsModelscomputational models
    Modeling Scenario
    217

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    6-029-TumorGrowth-ModelingScenario
    This modeling scenario guides a student familiar with single ordinary differential equation (ODE) models towards the development of a more complex system of two ODEs for describing the evolution of tumor growth over time.
    Pop_Growth Pilotlogisticcomparmenttumorsynthetic datasum of squares error
    Potential Scenario
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    2015-Heiko_Enderling-Integrating experimental data to calibrate quantitative cancer models
    For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer cells.
    cancertumorfittingagent-based
    Potential Scenario
    146

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    44

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    1999-Peter_Deuflhard-Differential Equations in Technology and Medicine
    It deals with a variety of challenging real life problems selected from clinical cancer therapy, communication technology, polymer production, and pharmaceutical drug design.
    cancerdesigntumordrugpolymertherapy
    Potential Scenario
    133

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    65

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    2013-Michael-Evans-Growth and Decay
    Sometimes, we can describe processes of growth and decay—whether physical, chemical, biological or sociological—by mathematical models.
    exponential growthexponential decayisotopespopulationsresource depletion
    Potential Scenario
    194

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    64

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    2011-Brian_Winkel-Parameter Estimates in Differential Equation Models for Population Growth
    We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and multiple species competition models.
    logisticpopulationparameciaGausegradient search
    Potential Scenario
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    60

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    1988-EY_Rodin-N_Taber-Yeast Growth Modelling in a Laboratory
    Modeling simple growth with some missing data and doing linear regression for parameter estimation in closed form solution of differential equation model and data.
    regressionyeastgrowth
    Potential Scenario
    156

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    50

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    2017-Lia_Vas-Modeling With Differential Equations
    This is a set of class notes for Lia Vas in which examples from population, falling objects, tank mixing, growth and threshold, are offered.
    thresholdsfalling objectgrowthtank mixing
    Potential Scenario
    220

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    2017-Rosario-Antony-Mathematical Model for Future Population Scenario In India And China – An Econometric Approach
    A mathematical model including dynamical systems, statistical models and differential equations involves variety abstract structures. Population growth is one of the main issues in India and China which are located in Asia.
    logisticIndiavital coefficientsAsiaCarrying Vapacitiyannual growth rate
    Potential Scenario
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    36

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    2004-Hill-Lozowski-Sampson-Experiments on ice spikes and a simple growth model
    We observed ice-spike growth using time-lapse digital photography, using two water types in two different containers.
    iceice spikebulk heat transfermass conservation
    Potential Scenario
    205

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    2004-Mitchell-von Meien-Krieger-Dalsenter-A review of recent developments in modeling of microbial growth kinetics
    Mathematical models are important tools for optimizing the design and operation of solid-state fermentation (SSF) bioreactors. Such models must describe the kinetics of microbial growth.
    Filamentous Fungisolid-state fermentationgrowth kineticsdiffusion-reactionoxygen transfer
    Potential Scenario
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    2015-Erzo-Luttmer-Four Models of Knowledge Diffusion and Growth
    This paper describes how long-run growth emerges in four closely related models that combine individual discovery with some form of social learning.
    knowledge diffusionstationary distributionsproductivity distributionreaction-diffusion equationsquasi-stationary distributions
    Potential Scenario
    150

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    47

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    2011-Kurt_Kreith-The Mathematics of Global Change
    The authors discuss broad issues and then focus on specifics like exponential growth, logistic growth, and the logistic equation with delay.
    exponential growthlogistic growth
    Potential Scenario
    138

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    51

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    1991-JR_Lobry-P_Flandois-Comparison of Monod's Growth Model Parameters from the Same Data Set
    The paper obtains the parameters in Monod's Growth model using a minimization of the sum of square errors with a given data set and obtains confidence intervals
    Confidence intervalssum of square errorslinearizationgrowthModo Growth model