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charlesrocabert/README.md

Hi there!

I am an evolutionary systems biologist, who uses computers and mathematics to explore the evolution of complex biological systems. I am studying how evolution shape genotypes, phenotypes and populations in changing environments, with their share of surprising and counter-intuitive effects.

Depending on their complexity, I usually consider simulation models as experimental systems (Peck, 2004) — I conduct in silico experiments in a computer as one would do in the real world (Hindré et al., 2012).

Check out my Github repositories to learn more about my ongoing modeling projects.

To find out more about me: https://charlesrocabert.github.io/.



« Simulations are experimental systems. Their complexity can make them closer cousins in complexity to nature itself than to simple analytic models, but with a powerful advantage over the real world: the modeler has complete control of the system. » (Peck, 2004).

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  1. MetEvolSim MetEvolSim Public

    MetEvolSim (Metabolome Evolution Simulator). A Python package to simulate the long-term evolution of metabolic levels.

    Python 5

  2. puutools puutools Public

    Easy-to-use C++ library for the live tracking of lineage and coalescence trees in individual-based forward-in-time simulations.

    C++

  3. MoRIS MoRIS Public

    MoRIS (Model of Routes of Invasive Spread). A simulator of human-mediated dispersal via transportation networks.

    C++ 4

  4. Evo2Sim Evo2Sim Public

    Digital evolution model dedicated to bacterial in silico experimental evolution.

    C++ 5

  5. SigmaFGM SigmaFGM Public

    Individual-based implementation of Fisher's geometric model with evolvable phenotypic noise.

    C++

  6. Koch-et-al-Predictability-of-Gene-Expression Koch-et-al-Predictability-of-Gene-Expression Public

    Tribolium castaneum transcriptomics pipeline developed for Koch et al. manuscript "Gene expression evolution is predicted by selection, genetic covariances and network topology".

    Python 1