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    1992-John_Mathews-Bounded population growth-a curve fitting lesson
    The purpose of this article is to present two methods for fitting the logistic curve to data supplied by the U. S. census bureau.

    Keywords: datalogisticlinearizationfitting

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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.

    Keywords: tumorgrowthGompertzfittingparameter

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    6-067-LotkaVolterra-ModelingScenario
    This modeling scenario guides students through the process of fitting the Lotka-Volterra model of two differential equations to a real time series observational data. Students use the capabilities...

    Keywords: time seriesdatacompetitionLotka-Volterramodel fittingpredictiongauseRexperimental

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    2009-Su-EtAl-Fitting Compartmental Models to Multiple Dose Pharmacokinetic Data using SAS
    In the case of a multiple dose study where subjects experience different dosing times, a superposition principle can be used to recursively account for each additional dose.

    Keywords: SASsuperpositionpharmacokineticscompartmental modelsmultiple dose

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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...

    Keywords: cancertumorfittingagent-based

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    2019-Hu-Treinen-One-step_method_for_modelling_longitudinal_data_with_differential_equations
    This study proposes a new approach to estimate the parameters in differential equation models used to describe non-linear trajectories of longitudinal data.

    Keywords: simulationparameter estimationshoppingfittingbehaviour

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    2017-D_Goulet-Modeling, Simulating, and Parameter Fitting of Biochemical Kinetic Experiments
    In many chemical and biological applications, systems of differential equations containing unknown parameters are used to explain empirical observations and experimental data. The differential...

    Keywords: optimizationBiochemistrysensitivity analysischromatographymass actioncluster analysisconservation lawsdimerizationestrogen receptor protein

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    Tree Biomass and Phenology
    This lesson centers around understanding the connection of tree biomass and phenology with climate change. It uses both swirl and LearnR lessons in the R programming language to help students make...
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    1-102-CancerTumor-ModelingScenario
    This module guides students in the use of differential equation models to predict cancer growth and optimize treatment outcomes. Several classical models for cancer growth are studied, including ...

    Keywords: optimizationlogisticpredictiondata fittingpower lawGompertzcancer growtheponentialBertalanaffy

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    Working with plant phenology data and fitting a nonlinear model using least squares in R
    A participatory live-coding lesson on working with NEON phenology data and fitting a sine-wave model to determine when different species get and lose their leaves.

    Keywords: modelingRphenologyNEONRstatscodeparticipatory live-coding

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    2008-Brewer-EtAl-Fitting ordinary differential equations to short time course data
    In this paper, we present a survey of existing algorithms and describe the main approaches. We also introduce and evaluate a new efficient technique for estimating ODEs linear in parameters...

    Keywords: time seriesEvaluation SPLINEgeneleast squaresbifurcation

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    Continuous Growth Models
    This Excel worksheet compares user-input growth data with predictions under linear, exponential, and logistic models of growth. Introduces concepts of statistical analysis that can be additionally...

    Keywords: exponential growthlogistic growthcurve fittinglinear growthgrowth models

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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...

    Keywords: optimizationcancerlogisticexponentialpredictiontumorgrowthdata fittingpower lawBertanffyGompertz

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    1-054-GrowthInFarmland-ModelingScenario
    An enriching project developing a model from data with missing temporal information is described. Students fit functions to the data that leads to the creation of a differential equations model,...

    Keywords: fittingfarmfarmland

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    2012-Transtrum-Qiu-Optimal experiment selection for parameter estimation in biological differential equation models
    We explore the question to what extent parameters can be efficiently estimated by appropriate experimental selection.

    Keywords: experimental designsystems biologyAssociation & Data Fittingreaction ratesdecay rates

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    Module M.4 Simple linear regression analysis
    Introduction to Primate Data Exploration and Linear Modeling with R was created with the goal of providing training to undergraduate biology students on data management and statistical analysis...

    Keywords: R programming languageprimatespopulation ecology

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    Design a Zoo (Grades 6-8)
    This classroom lesson presents students with the job of designing a zoo, which could include modeling tasks ranging from choosing and locating the exhibits to setting the right admission prices.
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    2017-Floyd_Ballard-Dice Activities for DE Models
    This document includes descriptions of four activities that are appropriate for a calculus or differential equations class, all using dice to motivate a differential equation model for a real-world...

    Keywords: simulationcurve fittingcdicecollect dataclass activitiesanalyze dataclass activity

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    1-005C-OilSlick-ModelingScenario
    We describe a modeling activity for Calculus I students in which modeling with difference and differential equations is appropriate.

    Keywords: Problem Solvingoil slickspreadfittinglineassumptions

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    1-066-USCensusModeling-ModelingScenario
    The United States Census, conducted every 10 years, gives data on the United States population, that can be modeled with the exponential, logistic, or Gompertz functions.

    Keywords: datalogisticpopulationGompertzcensusgoodness of fit

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