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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.
    Potential Scenario
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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).
    Potential Scenario
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    2018-Dyjuan_Tatro-The_Mathematics_of_Cancer-Fitting_Gompertz_Equation_to_Tumor_Growth
    Fitting the Gompertz Model to long term breast cancer study data, this project ascertains gompertzian parameters that can be used to predicts tumor growth as a function of time.
    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.
    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.
    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.
    Potential Scenario
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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.
    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.
    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.
    Potential Scenario
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    1969-Israelsson-Johnsson-Phase-shift in Geotropic Oscillations a Theoretical and Experimental Study
    The paper studies geotropical induced phase-shifts in circumnutations (turning) of Helianthus annus hypocotlys.
    Potential Scenario
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    2017-Bonin-EtAl-Mathematical modeling based on ordinary differential equations - promising approach to vaccinology
    As a proof of concept, we developed a model of the immune response to vaccination against the yellow fever. Our simulations have shown consistent results when compared with experimental data available in the literature.
    Potential Scenario
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    2016-Bonin-EtAl-Mathematical modeling based on ordinary differential equations-vaccinology
    We developed a model of the immune response to vaccination against the yellow fever. Our simulations have shown consistent results when compared with experimental data available in the literature.
    Potential Scenario
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    2017-Fred_Adler-Mathematically Modeling Asthma
    Our Asthma models have examined how a viral infection can tip the immune system into a different state, with the potential to predispose an individual to future asthma
    Modeling Scenario
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    1-081-TumorGrowth-ModelingScenario
    Students will transform, solve, and interpret a tumor growth scenario using non-linear differential equation models. Two population growth models (Gompertz and logistic) are applied to model tumor growth.
    Potential Scenario
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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.
    Potential Scenario
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    1999-Marchand-McDevitt-Learning Differential Equations by Exploring Earthquake Induced Structural Vibrations
    The project takes full advantage of analytical, numerical, and qualitative techniques to explore the mechanical vibrations of buildings during an earthquake.
    Potential Scenario
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    2017-Allali-EtAl-Mathematical Modeling of the Adaptive Immune Responses in the Early Stage of the HBV Infection
    The aim of this paper is to study the early stage of HBV infection and impact delay in the infection process on the adaptive immune response, which includes cytotoxic T-lymphocytes and antibodies.
    Modeling Scenario
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    6-017-OncolyticViruses-ModelingScenario
    Students explore oncolytic virotherapy using systems of differential equations and numerical simulations.
    Modeling Scenario
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    1-102C-CancerGrowth-ModelingScenario
    This module guides students in the use of differential equation models to predict cancer growth and study treatment outcomes. Several classical models for cancer growth are presented including exponential, power law, Bertalanffy, logistic, and...
    Modeling Scenario
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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.