BioModels: Content, Features, Functionality, and Use

Mathematical models play an important role in the interpretation and investigation of mechanisms underlying complex biological systems, and thereby in the understanding of human diseases. Using the ever increasing amount of high quality quantitative data produced in the Life Sciences, and experimentally rooted mathematical models and simulations, it is now possible to validate our current understanding of biological processes and to generate meaningful hypotheses for ill-defined processes. This in turn drives further experimental design. Mathematical modeling of biomolecular processes has become a standard part of the molecular and systems biologists’ toolkits. Wide availability and interoperability of models is seen as hugely important in an increasingly collaborative field. However, models covering even the same domain can exhibit much variation since different scientists have developed them at different periods, coming from different perspectives and using different conventions. To increase the reusability of existing published models, there has been a significant drive toward standardization of model encoding,