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    Potential Scenario
    155

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    77

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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.
    datalogisticlinearizationfitting
    Potential Scenario
    240

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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 scenario.
    simulationcurve fittingcdicecollect dataclass activitiesanalyze dataclass activity
    Modeling Scenario
    253

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    218

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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.
    datalogisticpopulationGompertzcensusgoodness of fit
    Potential Scenario
    148

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    81

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    2016-Mehmet_Pakdemirli-Mathematical design of a highway exit curve
    Using fundamental principles of physics and calculus, the differential equation determining the curve function is derived.
    kinematicscurve designhighway exittangential acceleration
    Modeling Scenario
    429

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    119

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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 of R and R studio.
    time seriesdatacompetitionLotka-Volterramodel fittingpredictiongauseRexperimental
    Potential Scenario
    162

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    83

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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.
    SASsuperpositionpharmacokineticscompartmental modelsmultiple dose
    Potential Scenario
    182

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    50

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    2012-Jambhekar-Breen-Extravascular Routes Of Drug Administration in Basic Pharamacokinetics
    This provides an excellent step-by-step of the physiology, construction of model, and notions like peak concentration as well as issues like lag time.
    concentrationphysiologydrugslag timeExtravascularPharamacokineticspeak time
    Potential Scenario
    200

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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 equations are typically nonlinear.
    optimizationBiochemistrysensitivity analysischromatographymass actioncluster analysisconservation lawsdimerizationestrogen receptor protein
    Potential Scenario
    155

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    87

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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
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    53

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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 particularly suited to situations where noise levels are...
    time seriesEvaluation SPLINEgeneleast squaresbifurcation
    Potential Scenario
    115

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    51

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    1987-Claude-Marmasse-Studies on differential equations of enzyme kinetics-Biomolecular scheme
    The integral curve is compared with the solutions given by the two classical approximations to the problem: it is shown that the steady-state approximation is to be preferred to the rapid equilibrium theory as a general method.
    steady-state modelisoclinesenzyme kinetics
    Modeling Scenario
    386

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    398

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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 exponential, power law, Bertalanffy, logistic, and...
    optimizationlogisticpredictiondata fittingpower lawGompertzcancer growtheponentialBertalanaffy
    Modeling Scenario
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    272

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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...
    optimizationcancerlogisticexponentialpredictiontumorgrowthdata fittingpower lawBertanffyGompertz
    Potential Scenario
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    49

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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.
    experimental designsystems biologyAssociation & Data Fittingreaction ratesdecay rates
    Potential Scenario
    166

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    89

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    2018-Akman-EtAl-Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization
    We demonstrate Particle Swarm Optimization efficacy by showing that it outstrips evolutionary computing methods previously used to analyze an epidemic model.
    epidemicParticle Swarm Optimizationoptimize parameters
    Potential Scenario
    148

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    44

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    2010-Singh-Mishra-athematical modeling approach to study growth rate of grassroots technological innovations
    In this paper we have proposed a simple mathematical model by using ordinary differential equation to know the spread rate of technological innovations in rural India.
    logisticexponentialsigmoidtechnological innovationsasymptoticspread of innovation
    Technique Narrative
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    2-005-LinearizeItAll-TechniqueNarrative
    Linear approximations are often used to simplify nonlinear ordinary differential equations (ODEs) for ease in analysis. The resulting linear approximation produces an ODE where closed form solutions may be obtained.
    computationerrorTorricelli's Lawdata fittinglinear approximation
    Modeling Scenario
    368

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    221

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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.
    Problem Solvingoil slickspreadfittinglineassumptions
    Modeling Scenario
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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, which they then are required to analyze in multiple...
    fittingfarmfarmland
    Potential Scenario
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    2015-Doust-Saraj-The logistic modeling population having harvesting factor
    The present paper deals with the logistic equation having harvesting factor, which is studied in two cases constant and non-constant.
    logisticharvestharvesting factor