The goal of computational systems biology is to develop models that can
predict and explain uknown facts about the dynamics of biological systems,
especially, non-trivial behaviour emerging from the interplay among the
enormous number of individual biochemical components. Models are typically
based on known first principles, wet-lab measurements, and existing hypotheses
available in literature. An important precondition of a successful systems
biology project is compilation of known and hypothesised knowledge about the
system in the form of a formal specification understandable to experts from
different disciplines. Such a specification then allows to rigorously
integrate the models with experimental data and advanced analysis techniques.
In this fashion, we develop the online modelling platform for cyanobacteria
processes called e-cyanobacterium.org. In this presentation, we will give an
overview of the platform and related technologies: the biochemical space
language for compact representation of biological processes with relations to
existing ontologies, formal methods for exploration of models with uncertain
parameters, and related high-performance tools developed in our laboratory.
Finally, an overview of case studies and ongoing applications will be given.