The Center for Reproducible Biomedical Modeling has a new publication, Practical Resources for Enhancing the Reproducibility of Mechanistic Modeling in Systems Biology. It is now available on ResearchGate.
Authors:
Michael Blinov, John Gennari, Jonathan Karr, Ion Moraru, David Nickerson, Herbert Sauro
Highlights
- • Reproducibility is critical to the advancement of computational modeling.
- • The current high degree of irreproducibility reduces the impact of many studies.
- • Easy access, community standards, annotation, and curation promise to foster reproducibility.
- • Better reproducibility would extend the lifespan of many studies.
- • Repeating a study using the same data and software should be a requirement for a publication.
Abstract
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 biology 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. In turn, we believe enhanced reproducibility would accelerate the development of more sophisticated models that could inform precision medicine and synthetic biology.