Semantic Systems Biology

Mission: Elucidate mechanisms underlying basic cellular processes, evolution and interactions among microbes and between microbes and their environment (including the human host) and to translate this knowledge into applications of biotechnological, medical and environmental interest.

We align and integrate heterogeneous data and develop models supporting decision making and design strategies. We combine top-down and bottom-up approaches together with data integration approaches to design subsequent experiment and intervention strategies.

We deploy semantic web technologies for heterogeneous data integration in the life sciences. Two main type of research outputs are produced: i) biological applications, addressing biological questions, and ii) technological developments: tools, models and infrastructures required to address  the challenges in i).

Selected biological applications:

UNDER construction


Technological developments: Semantic Web tools

van Dam et al. Interoperable genome annotation with GBOL, an extendable infrastructure for functional data mining (GBOL) Preprint available at bioRxiv

Koehorst et al. (2017)  SAPP: functional genome annotation and analysis through a semantic framework using FAIR principles.  Bioinformatics btx767

Benis et al 2016. Building Pathway Graphs from BioPAX Data in R. F1000Research 5

van Heck et al 2016 Efficient reconstruction of predictive consensus metabolic network models PloS Computational Biol.

van Dam, et al . 2015. RDF2Graph a Tool to Recover, Understand and Validate the Ontology of an RDF Resource. Journal of Biomedical Semantics 6: 39.