Jon Darkow's Work
We found 122 items
Include in results:
#2
1592316.6
Enzyme Diversity: Enzymes, Products, and Substrates
by Jon Darkow
sim
⋮ 1,120,614 runs
enzymes
substrates
products
DNA
trypsin
#3
791428.9
Cellular Respiration Accounting Model
by Jon Darkow
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in i
... Read more
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in its chemical bonds is transfered.
sim
⋮ 720,330 runs
cellular respiration
aerobic respiration
ATP
biology
#4
727375.06
#6
567712.2
Lactase with Variable Sample Sizes
by Jon Darkow
Arrayed Lactase Model
sim
⋮ 845,960 runs
Lactase
array
sample size
biology
#7
451861.88
Information Processing and Neurophysiology Model
by Jon Darkow
The main dependent variable measured in the model is the membrane potential (millivolts) of two diff
... Read more
The main dependent variable measured in the model is the membrane potential (millivolts) of two different neurons in a series. You will be able to add excitatory and inhibitory neurotransmitters, and compare how these modulate electrical impulses of the two neurons.
Additionally, you will be able to compare the effects of three neurotoxins: Tetrodotoxin, botulinum toxin, and sarin nerve gas. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
sim
⋮ 307,321 runs
infromation processing
neurophysiology
biology
#8
364673.78
Lotka-Volterra Predator-Prey Model
by Jon Darkow
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by t
... Read more
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by the interconnections of a negative feedback loop governs much of life.
sim
⋮ 282,659 runs
negative feedback loop
Lotka-Volterra
homeostasis
predator-prey
#10
286690.53
Growth Factors, Cyclins, and Cancer
by Jon Darkow
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (gro
... Read more
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (growth factors), to stimulate the cell cycle feedback loops.
sim
⋮ 307,661 runs
growth factors
cyclins
cell cycle
cancer
#11
190023.9
Evolution of Antibiotic Resistance Simulation
by Jon Darkow
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of
... Read more
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of bacteria. The main purpose of the model is to show that new adaptations are not caused by an environmental factor, like antibiotics. Rather, new adaptations are the selection of available variations. In this model you can increase variations by increasing the UV dose. The UV dose increases the mutation rate with a Monte Carlo function.
sim
⋮ 191,566 runs
Biology
Science
Ecology
Education
#12
166701.03
Lactose Operon: An Inducible System
by Jon Darkow
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteri
... Read more
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteria. Lactose induces the system by inhibiting and inhibitor.
sim
⋮ 145,914 runs
Inhibition
negative feedback
biology
lactose
operon
#13
138575.45
Apterous Genetics
by Jon Darkow
Apterous is an allele that results in a fly without wings. Wild-type variants have normally function
... Read more
Apterous is an allele that results in a fly without wings. Wild-type variants have normally functioning wings.
The goal of this simulation is to determine the pattern of inheritance for the apterous phenotype. Is apterous dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
sim
⋮ 308,160 runs
Genetics
#14
134173.27
Limiting Nutrients in Aquatic Ecosystems
by Jon Darkow
Experiment with a variety of nutrients that are limited by different degrees in four different ecosy
... Read more
Experiment with a variety of nutrients that are limited by different degrees in four different ecosystems.
sim
⋮ 129,866 runs
limiting nutrients
ecosystem
biology
logistic growth
#15
119811.2
#16
118786.625
Diffusion of a Spherical Cell
by Jon Darkow
Why are cells small? This model allows users to see how the size of a sphere affects the rate of dif
... Read more
Why are cells small? This model allows users to see how the size of a sphere affects the rate of diffusion.
sim
⋮ 146,029 runs
diffusion
surface area
volume
radius
#17
107242.625
Transformation Simulation
by Jon Darkow
Simulation allows students to test the transformation principle. Two major goals of the experiment a
... Read more
Simulation allows students to test the transformation principle. Two major goals of the experiment are:
1. Allow users to see that supernatant from heat-killed bacteria can transform the genes of another bacterium.
2. What transforms the inheritance of the bacteria is DNA, not RNA or proteins.
sim
⋮ 135,566 runs
transformation
DNA
biology
#18
103050.13
Water Potential and Osmosis
by Jon Darkow
Factors that affect the flow across a semi-permeable membrane.
sim
⋮ 397,870 runs
#20
87150.84
Cellular Respiration Inquiry
by Jon Darkow
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computa
... Read more
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computations.
sim
⋮ 113,215 runs
metabolism
respriation
ATP
biology
#22
81288.49
White-Eyed Genetics
by Jon Darkow
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes.
The
... Read more
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes.
The goal of this simulation is to determine the pattern of inheritance for the white-eyed phenotype. Is yellow body dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
sim
⋮ 190,621 runs
Genetics
#23
81203.625
Neurophysiology and Neurotoxicity
by Jon Darkow
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor
... Read more
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor neuron and the muscle fiber it innervates. You will be able to add excitatory and inhibitory neurotransmitters, and compare how neurotransmitters modulate the electrical impulses of the motor neuron and the muscle fiber.
Additionally, you will be able to compare the effects of four neurotoxins: Tetrodotoxin, botulinum toxin, sarin nerve gas, and VX. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
sim
⋮ 46,458 runs
Neurophysiology
toxins
sarin
VX
TTX
#24
77148.97
Thyroid Hormone - Negative Feedback
by Jon Darkow
sim
⋮ 80,226 runs
negative feedback
thyroid hormone
metabolism
biology
#26
65246.996
The dynamics of photosynthesis - variable sample size
by Jon Darkow
The dynamics of photosynthesis - variable sample size
sim
⋮ 94,097 runs
photosynthesis
sample size
biology
#29
53333.094
Evolution of LAP Allele in Mussels
by Jon Darkow
sim
⋮ 85,305 runs
Evolution
Natural Selection
Cline
#30
47106.13
Photosynthesis with Variable Sample Sizes
by Jon Darkow
Sample sizes of Photosynthesis stocks in an array
#31
38116.33
Genotyping with Electrophoresis
by Jon Darkow
sim
⋮ 44,029 runs
biology
inheritance
DNA
restriction enzyme
#33
36498.453
Transformation Experiment with Controls
by Jon Darkow
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griff
... Read more
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griffith.
sim
⋮ 29,625 runs
Biology
Science
Education
transformation
DNA
#35
28643.04
#37
27436.1
SIR COVID-19 Coronavirus Simulation
by Jon Darkow
sim
⋮ 18,919 runs
Environment
Biology
Science
Education
SIR
#39
24296.5
Neurophysiology and Information Processing 2022
by Jon Darkow
sim
⋮ 20,192 runs
Biology
information processing
neuron
neurotransmission
neurophysiology
#42
19437.74
Phenology of the Karner Blue Butterfly
by Jon Darkow
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing fac
... Read more
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing factors to the reduction in the butterflies' population sizes. Climate change can alter the timing of lifecycles. When climate change disproportionally affects the timing of life cycles of species in an ecosystem asynchrony within a food web occurs.
sim
⋮ 12,496 runs
asynchrony
timing
phenology
climate change
butterfly
#43
17732.215
HPV with Influenza A Humoral Immunity
by Jon Darkow
Immune response of HPV
sim
⋮ 27,986 runs
HPV
antibodies
biology
Immunity
#45
14866.037
Circadian Clock in the Mouse
by Jon Darkow
Transcriptional Translational Feedback Loop in the Mouse
sim
⋮ 31,054 runs
Mouse
Circadian
Clock
#46
12712.289
System Dynamics of Carbon Budget
by Jon Darkow
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems d
... Read more
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems dynamics based on John Sternman (MIT) and Krytyna Stave (University of Nebraska)
sim
⋮ 16,561 runs
system dynamics
carbon
climate
#47
10084.604
Carbon Cycle Simulation
by Jon Darkow
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can
... Read more
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can manipulate with graphical inputs the changes in fossil fuel emissions, land-use, and ocean sinks.
sim
⋮ 10,193 runs
Environment
Biology
Science
Ecology
Education
#48
9771.8
Evolution: Grants Finches
by Jon Darkow
Models the effects on population sizes of ground finches with different beak sizes in response to di
... Read more
Models the effects on population sizes of ground finches with different beak sizes in response to different amounts of annual precipitation.
sim
⋮ 12,416 runs
evolution
biology
natural selection
#50
8525.167
HPV and Adaptive Immune Response
by Jon Darkow
sim
⋮ 12,022 runs
HPV
Antibodies
feedback loops
vaccine
#52
6644.9614
Evolution with Heterozygous Advantage
by Jon Darkow
Evolution of Populations: Genetic Drift, Natural Selection, and Mutations
sim
⋮ 7,692 runs
evolution
natural selection
genetic drift
#53
4510.2334
Logistic Growth Model and the Butterfly Effect
by Jon Darkow
Model allows users to test the starting population size (N), the carrying capacity of the populatio
... Read more
Model allows users to test the starting population size (N), the carrying capacity of the population (K), and the intrinsic rate of growth (r max).
Iterations are discrete, not continuous.
sim
⋮ 6,155 runs
logistic growth
carrying capacity
#56
2823.6694
Bathtub Dynamics
by Jon Darkow
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model
... Read more
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model 2 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub.
Model 3 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub. However, Model 3 uses Torricelli's law to calculate the flow rate based on physical principles.
This law was formulated by Evangelista Torricelli, an Italian physicist, in the 17th century. It's an important principle in fluid dynamics and is closely related to Bernoulli's principle. Torricelli's law states that the speed (velocity) of efflux of a fluid through a hole under the force of gravity is proportional to the square root of the vertical distance (height) between the fluid surface and the center of the hole. The formula is given by efflux velocity = 2*g*ℎ, where:
g is the acceleration due to gravity (approximately 9.81 m/s² on Earth).
ℎ is the height of the fluid column above the hole.
The idea is that the fluid's potential energy due to its height is converted into kinetic energy as it falls. The higher the fluid, the greater its potential energy and thus the greater the speed at which it exits the hole. This principle is used in various applications, such as determining the flow rate of liquids from tanks, in hydrodynamics studies, and even in everyday situations like draining a bathtub. The law assumes an ideal fluid (incompressible and non-viscous) and neglects factors like air resistance and the viscosity of the fluid. It also assumes that the size of the hole is small compared to the depth of the fluid.
The flow rate (the volume of fluid flowing per unit time) can be calculated by multiplying the cross-sectional area of the hole (A) by the velocity of the fluid (v), leading to the formula
Q=A*v, where Q is the flow rate.
sim
⋮ 1,015 runs
Environment
Science
Education
Bathtub
hydrodynamics
#57
2296.8997
Phosphorus in Lake: Changes to Flows in a Dynamic System
by Jon Darkow
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a
... Read more
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a lake), an inflow (added P/day), and an outflow (removed P/day).
The flows can either be constant throughout the simulation run, or dynamic (changing throughout the simulation run.)
sim
⋮ 3,171 runs
flows
dynamic
phosphorus
#58
1836.8276
Chaos Theory: Strange Attractor
by Jon Darkow
Manipulate the main variables of the Lorenz equation.
sim
⋮ 2,382 runs
chaos theory
Lorenz
attractor
manifold
#60
1684.925
Evolving Bits
by Jon Darkow
Diversity and selection for the basis of evolution. This simple model tries to illustrate these conc
... Read more
Diversity and selection for the basis of evolution. This simple model tries to illustrate these concepts.
sim
⋮ 1,666 runs
Diversity
Selection
Evolution
Receptor
Antigen
#61
1510.22
Differential Reproduction, Natural Selection Model
by Jon Darkow
This is the fourth model in a sequence of models to show the logic of natural selection, formalized
... Read more
This is the fourth model in a sequence of models to show the logic of natural selection, formalized by Earnst Mayr.
Mayr E. The growth of biological thought. Cambridge: Harvard University Press; 1982.
#63
1140.2546
Understanding Linear Motion
by Jon Darkow
Understand linear motion with automated feedback.
sim
⋮ 1,111 runs
Science
Education
physics
motion
velocity
#66
750.176
Tick Tock: The Biological Clock and Circadian Rhythm
by Jon Darkow
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circa
... Read more
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circadian rhythm.
sim
⋮ 1,128 runs
circadian
clock
feedback loop
#67
719.6
SIR Model for Coronavirus (COVID-19) - with social distancing
by Jon Darkow
This model was copied from Jon Darkow:
#71
615.06433
Endocrine System Dynamics
by Jon Darkow
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge fr
... Read more
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge from underproduction and excess production of the hormone.
This model was developed for a high school Anatomy and Physiology class.
#72
587.6
#76
522.12
Mechanical Energy and Kinematics
by Jon Darkow
sim
⋮ 419 runs
Science
Physics
Energy
Acceleration
Velocity
#78
477.696
SIR Model for COVID-19
by Jon Darkow
This model was copied from Jon Darkow:
This model was copied from Jon Darkow:
#79
432.64334
#80
388.74167
Fruit Fly Choice
by Jon Darkow
Simulation to model random behavior in a fruit fly choice chamber
sim
⋮ 1,019 runs
randomness
random
#81
351.29333
Gravitational Attraction of Three Bodies
by Jon Darkow
sim
⋮ 371 runs
Science
Education
Forces
Gravitation
Physics
#95
208.90334
#99
199.16
#102
177.08667
#107
122.84
Beta Cell Membrane Transport - Insulin Regulation
by Jon Darkow
sim
⋮ 269 runs
Insulin
Glucose
Beta Cell
#108
80.7
Soybean and Aphid Dynamics
by Jon Darkow
sim
⋮ 108 runs
Environment
Biology
Science
Economics
Ecology
#109
58.993332
Body Temperature Regulation with Scatter Plot
by Jon Darkow
sim
⋮ 140 runs
Biology
Science
Education
Health
#110
56.44
Photosynthesis Simulation - Simplified
by Jon Darkow
sim
⋮ 85 runs
Environment
Biology
Science
Ecology
Education
#111
26.690666
Stock, Inflow, and Outflow with Atrazine
by Jon Darkow
Simple stock and flow diagram. Flows linear.
sim
⋮ 86 runs
stock
flow
atrazine
#116
6.47
Pendulum Model
by Jon Darkow
sim
⋮ 17 runs
Science
Education
Physics
Simple Harmonic Motion
Pendulum
Uploading a Bundle from Zip
Instead of creating bundles, categories, and assemblies one by one, you can upload a single zip file that contains all of your bundle's content. To create your zipped bundle, make a folder with your bundle's name and add subfolders with your categories' names. The folder tree should have the same structure that you want the categories to have in your bundle. Place your assembly .stmx files in the appropriate category folders, then zip your bundle folder and upload it using the Upload Bundle from Zip link above.
Assemblies, Bundles, and Categories
Assemblies are self contained models that demonstrate common ways to connect together building blocks and that can be used as parts of other models. This is analogous to using prefabricated wall and roof pieces to construct a house.
Bundles are groups of assemblies with a common use or theme. For example, a Health Care bundle might contain a variety of assemblies that aid in creating health care models. When you download assemblies from the isee Exchange™, you download an entire bundle, rather than individual assemblies.
Categories are subgroups of assemblies within a bundle. For example, a Health Care bundle might contain a Funding category for assemblies related to the management of hospital funds. All assemblies must be assigned to a category—they cannot be assigned to the root of a bundle.
Assemblies, bundles, and categories can be created and uploaded to the isee Exchange™ via the options on the Manage My Assemblies page. To learn more, visit our help pages, or take our assemblies tutorial.
Sim App (Sim)
An interface that allows users to interact with a model.
Sim apps allow users to interact with a model using buttons, sliders, knobs, tables, graphs, and storytelling. These interactions help users understand how parts of a system interact.
Interfaces are created by model authors in the Stella desktop software and can be uploaded to the isee Exchange™.
Model
A diagram that represents how elements in a system influence one another.
Models are mathematical representations of how elements in a system are connected and interact (e.g., ecosystems, organizations, supply chains). When running models on the isee Exchange™, results can be viewed in output devices like graphs and tables.
Models appear in the isee Exchange™ directory when authors upload them from the Stella® desktop software or create them with Stella Online™.
Causal Loop Diagram (CLD)
A map that represents the feedback structure of a system.
CLDs are high-level maps that represents the feedback structure of a system and easily communicate the essence of a model. They appear in the isee Exchange™ when authors upload them from the Stella desktop software or create them with Stella Online™.