To cite MGDrivE in publications use:

S├ínchez Castellanos H, Bennett J, Wu S, Marshall J (2019). “MGDrivE: A modular simulation framework for the spread of gene drives through spatially-explicit mosquito populations.” bioRxiv. doi: 10.1101/350488, https://www.biorxiv.org/content/early/2019/04/11/350488.full.pdf, https://www.biorxiv.org/content/early/2019/04/11/350488.

Corresponding BibTeX entry:

  @Article{,
    title = {MGDrivE: A modular simulation framework for the spread of
      gene drives through spatially-explicit mosquito populations},
    author = {H{\'e}ctor Manuel {S{\'a}nchez Castellanos} and Jared
      Bennett and Sean Wu and John M. Marshall},
    year = {2019},
    doi = {10.1101/350488},
    publisher = {Cold Spring Harbor Laboratory},
    abstract = {Malaria, dengue, Zika, and other mosquito-borne
      diseases continue to pose a major global health burden through
      much of the world, despite the widespread distribution of
      insecticide-based tools and antimalarial drugs. The advent of
      CRISPR/Cas9-based gene editing and its demonstrated ability to
      streamline the development of gene drive systems has reignited
      interest in the application of this technology to the control of
      mosquitoes and the diseases they transmit. The versatility of
      this technology has also enabled a wide range of gene drive
      architectures to be realized, creating a need for their
      population-level and spatial dynamics to be explored. To this
      end, we present MGDrivE (Mosquito Gene Drive Explorer): a
      simulation framework designed to investigate the population
      dynamics of a variety of gene drive architectures and their
      spread through spatially-explicit mosquito populations. A key
      strength of the MGDrivE framework is its modularity: a) a genetic
      inheritance module accommodates the dynamics of gene drive
      systems displaying user-defined inheritance patterns, b) a
      population dynamic module accommodates the life history of a
      variety of mosquito disease vectors and insect agricultural pest
      species, and c) a landscape module accommodates the distribution
      of insect metapopulations connected by migration in space.
      Example MGDrivE simulations are presented to demonstrate the
      application of the framework to CRISPR/Cas9-based homing gene
      drive for: a) driving a disease-refractory gene into a population
      (i.e. population replacement), and b) disrupting a gene required
      for female fertility (i.e. population suppression), incorporating
      homing-resistant alleles in both cases. We compare MGDrivE with
      other genetic simulation packages, and conclude with a discussion
      of future directions in gene drive modeling.},
    url = {https://www.biorxiv.org/content/early/2019/04/11/350488},
    eprint =
      {https://www.biorxiv.org/content/early/2019/04/11/350488.full.pdf},
    journal = {bioRxiv},
  }