  Background: The study of genome-scale metabolic models and their underlying
networks is one of the most important fields in systems biology. The complexity
of these models and their description makes the use of computational tools an
essential element in their research. Therefore there is a strong need of
efficient and versatile computational tools for the research in this area.
  Results: In this manuscript we present PyNetMet, a Python library of tools to
work with networks and metabolic models. These are open-source free tools for
use in a Python platform, which adds considerably versatility to them when
compared with their desktop software similars. On the other hand these tools
allow one to work with different standards of metabolic models (OptGene and
SBML) and the fact that they are programmed in Python opens the possibility of
efficient integration with any other already existing Python tool.
  Conclusions: PyNetMet is, therefore, a collection of computational tools that
will facilitate the research work with metabolic models and networks.
