@article{Gloeckler2023,
  author   = {Gl\"ockler, Manuel and Dr\"ager, Andreas and Mostolizadeh, Reihaneh},
  title    = {{Hierarchical modelling of microbial communities}},
  journal  = {Bioinformatics},
  volume   = {39},
  number   = {1},
  year     = {2023},
  month    = jan,
  url      = {https://academic.oup.com/bioinformatics/article/39/1/btad040/6992661},
  doi      = {10.1093/bioinformatics/btad040},
  eprint   = {https://academic.oup.com/bioinformatics/article-pdf/39/1/btad040/48959105/btad040.pdf},
  pdf      = {https://academic.oup.com/bioinformatics/article-pdf/39/1/btad040/48959105/btad040.pdf},
  issn     = {1367-4811},
  keywords = {Hierarchical modelling; SBML; NCMW; Python; Systems biology},
  abstract = {Summary: The human body harbours a plethora of microbes that play a
    fundamental role in the well-being of the host. Still, the contribution of many
    microorganisms to human health remains undiscovered. To understand the composition of
    their communities, the accurate genome-scale metabolic network models of participating
    microorganisms are integrated to construct a community that mimics the normal
    bacterial flora of humans. So far, tools for modelling the communities have
    transformed the community into various optimisation problems and model compositions.
    Therefore, any knockout or modification of each submodel (each species) necessitates
    the up-to-date creation of the community to incorporate rebuildings. To solve this
    complexity, we refer to the context of SBML in a hierarchical model composition,
    wherein each species's GEM is imported as a submodel in another model. Hence, the
    community is a model composed of submodels defined in separate files. We combine all
    these files upon parsing to a so-called ``flattened'' model, i.e., a comprehensive and
    valid SBML file of the entire community that COBRApy can parse for further processing.
    The hierarchical model facilitates the analysis of the whole community irrespective of
    any changes in the individual submodels.
    Availability: The module is freely available within the Nasal Community Modelling
    Workflow (NCMW) package at https://github.com/manuelgloeckler/ncmw.
    Contact: reihaneh.mostolizadeh@uni-tuebingen.de},
}