  Although reproducibility is a core tenet of the scientific method, it remains
challenging to reproduce many results. Surprisingly, this also holds true for
computational results in domains such as systems biology where there have been
extensive standardization efforts. For example, Tiwari et al. recently found
that they could only repeat 50% of published simulation results in systems
biology. Toward improving the reproducibility of computational systems
research, we identified several resources that investigators can leverage to
make their research more accessible, executable, and comprehensible by others.
In particular, we identified several domain standards and curation services, as
well as powerful approaches pioneered by the software engineering industry that
we believe many investigators could adopt. Together, we believe these
approaches could substantially enhance the reproducibility of systems biology
research. In turn, we believe enhanced reproducibility would accelerate the
development of more sophisticated models that could inform precision medicine
and synthetic biology.
