The use of computational modeling to describe and analyze biological systems is at the heart
of systems biology. Model structures, simulation descriptions and numerical results can be …

Abstract Systems biology has experienced dramatic growth in the number, size, and
complexity of computational models. To reproduce simulation results and reuse models, …

Background The increasing use of computational simulation experiments to inform modern
biological research creates new challenges to annotate, archive, share and reproduce such …

Reproducibility of experiments is a basic requirement for science. Minimum Information (MI)
guidelines have proved a helpful means of enabling reuse of existing work in modern …

Background With the ever increasing use of computational models in the biosciences, the
need to share models and reproduce the results of published studies efficiently and easily is …

Computational models can help researchers to interpret data, understand biological functions,
and make quantitative predictions. The Systems Biology Markup Language (SBML) is a …

Biomedical data are amassed at an ever-increasing rate, and machine learning tools that
use prior knowledge in combination with biomedical big data are gaining much traction 1, 2. …

The Computational Modeling in Biology Network (COMBINE) is a consortium of groups
involved in the development of open community standards and formats used in computational …

Computational models can help researchers to interpret data, understand biological functions,
and make quantitative predictions. The Systems Biology Markup Language (SBML) is a …

Background Thorough data stewardship is a key enabler of comprehensive health research.
Processes such as data collection, storage, access, sharing, and analytics require …