Publication details

E-cyanobacterium.org: A Web-based Platform for Systems Biology of Cyanobacteria

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Authors

TROJÁK Matej ŠAFRÁNEK David HRABEC Jakub ŠALAGOVIČ Jakub ROMANOVSKÁ Františka HAJNAL Matej ČERVENÝ Jan

Year of publication 2017
Type Appeared in Conference without Proceedings
MU Faculty or unit

Faculty of Informatics

Citation
Description The understanding of a complex cellular machinery is a crucial problem in current systems biology, especially for photosynthetic organisms such as cyanobacteria. To challenge this uneasy task we have developed an online platform which consists of three interconnected modules. • Biochemical Space (BCS) allows to formally describe (bio)chemical reactions facilitated by cyanobacteria molecular entities. Such reactions are represented in a generalised form of rules specified in the Biochemical Space Language – a novel rule-based language. The rules form a hierarchy of (bio)chemical processes covering transport, metabolism, circadian clock, photosynthesis, and carbon concentrating mechanism. • Model Repository is a collection of related mathematical models accompanied with simulation and static analysis algorithms. Linkage of model components to BCS determines their exact biological meaning. This feature is also present in models exported to SBML standard format. • Experiments Repository serves to import, store, and plot time-series experiments. The measured variables are connected to BCS in the same manner as in the case of model components. Individual experiments possess additional references to related models. In addition, data annotation is available in all modules of the platform. In consequence, BCS, models, and experiments are well-noted and referenceable. Moreover, the usability of the platform is enhanced with visualisations provided for process hierarchy and reaction networks in BCS, simulations in Model Repository, and time-series plots in Experiment Repository. In conclusion, our platform provides a unique solution based on integrating three different approaches to stimulate collaboration between experimental and computational systems biologists.
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