Brett and Bas are co-authors on a new paper in Molecular Systems Biology describing the latest developments in model encoding in systems biology. Bas enthusiastically supports the use of standards in systems biology while Brett has been active in the SBML field for 15 years as a community member, specification writer, package coordinator (FBC), libSBML developer, editor and SBML team member.
This paper provides an overview of the modelling frameworks, tools and facilities that are central to the SBML community.
“Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose.
A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models.
The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. “
Moritz Bieber, Christian Lieven (Biosustain, DTU), Brett Olivier and Bas Teusink (AIMMS, VU Amsterdam) and a worldwide community of scientists developed quality control tools for systems biology models in Nature Biotechnology
Mathematical models are key tool to
understand complex biological systems. In particular, constraint-based, genome
scale, models (GSM’s) can relate the physiological property of a cells, such as
growth and metabolism, to the chemical flows through the underlying metabolic
reaction network encoded by the genes. However, each model can in itself
contain thousands of components. Moreover there is a continuous increase in
number of these models being produced, using various semi-automated methods.
The question arises, how do you evaluate a models quality? Being able to answer
this question is critical to a model’s reproducibility and reusability.
In a recent correspondence published in Nature Biotechnology Moritz Bieber, Christian Lieven (Biosustain, DTU) and a large, worldwide community of scientists including Brett Olivier and Bas Teusink (AIMMS, VU Amsterdam) set out to address this problem. The tool presented in this contribution, MEMOTE, leverages the advantages of the latest community developed model encoding standards (SBML FBC), and implements a pipeline containing a set of tests that evaluates a model’s annotation, basic functionality and conceptual integrity. Hopefully, this will lead to a more efficient (re)use of genome-scale models in research and biotechnology.