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Biology in Code

Computational biology simulations for evolution, genetic distributions, and epidemic spread using stochastic modeling and data visualization.

PythonNumPyMatplotlibSimulation

Overview

Biology in Code is a simulation playground for modeling biological systems as executable experiments. Instead of static textbook examples, each scenario is represented as a probabilistic process that can be inspected and iterated on.

What was built

  • Monte Carlo style simulations for inheritance and population-level trait shifts.
  • Evolutionary process models showing selection pressure and drift over multiple generations.
  • Epidemiological spread experiments with adjustable transmissibility and recovery parameters.
  • Visualization pipelines for comparing parameter choices and emergent behavior.

Impact

  • Turned abstract biological intuition into reproducible, inspectable code.
  • Created a reusable base for future education-focused scientific demos.

Demo

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