How do I simulate an insulin response?

Open this page and use the live Genetics Lab tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.

Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.

Can I use my own numbers?

Absolutely — every input is adjustable, and with data import you can drive an insulin response from your own measurements.

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Genetics Lab for an insulin response

Simulate an insulin response live in your browser. This runs the real Genetics Lab solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

For:Students Researchers Educators Engineers Hobbyists & Makers K-12 Students First Responders

Hardy Weinberg

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Hardy-Weinberg & SelectionLive

population genetics

Controls

Presets

Initial freq of A (p₀)

Fitness AA

Fitness Aa

Fitness aa

Without selection, allele frequencies stay put and genotypes settle at p², 2pq, q² — Hardy-Weinberg equilibrium. Give the genotypes different fitness and selection shifts the allele frequency each generation. Heterozygote advantage (high Aa fitness) can hold both alleles in a stable balance.

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Data Inspector

Final freq A0.500

Outcomepolymorphic

Mean fitness0.95

Governing equation

p^{2} + 2 pq + q^{2} = 0.25 + 0.50 + 0.25 = 1 (p = 0.5, q = 0.50)

Reading this result: Allele A is favored at every genotype, so directional selection drives p toward 1 and eventually fixes A.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Genetic Drift

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Genetic Drift (Wright-Fisher)Live

chance changes allele frequencies

Controls

Presets

Population size N

Initial frequency p₀

Replicate populations

Even with no selection, allele frequencies wander purely by chance as each generation is randomly sampled from the last. In small populations this genetic drift is fast and alleles quickly fix or vanish; in large populations it is slow. Each colored line is an independent population starting from the same frequency.

▶ Run in Python

Data Inspector

Fixed (reached 1)0

Lost (reached 0)0

Population size50

Governing equation

Var (p) = \frac{p _{0} ( 1 - p _{0} )}{2 N} = \frac{0.5 ( 1 - 0.5 )}{2 \cdot 50} = 0.0025

Reading this result: Over many replicates the fraction that fix an allele converges on its starting frequency p₀=0.5 — drift is directionless, but the odds of fixation equal where you began.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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About this simulation

The full Genetics Lab tool models an insulin response with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

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Other ways to simulate an insulin response

Dynamical Systems for an insulin response Epidemic Network for an insulin response Spatial Predator–Prey for an insulin response SIR Epidemic for an insulin response Hodgkin-Huxley Neuron for an insulin response Lotka-Volterra for an insulin response

Frequently asked questions

How do I simulate an insulin response?: Open this page and use the live Genetics Lab tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?: Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?: Absolutely — every input is adjustable, and with data import you can drive an insulin response from your own measurements.