Abstract
A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the Bricks Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.
Highlights
To better understand how complex biological systems work, we need to represent our knowledge in a clear and unambiguous form that is accessible to both scientists and computational agents
Continuing with our example, the green bricks constituting the map of Figure 1 are instances of a template brick that is a canonical representation of the concept described by the term “protein phosphorylation”
56% of these instances could not be matched to more specific template bricks for reasons independent to the ontology: we found that 26% were misrepresentations, 30% represented processes whose nature was implicitly given by the labels of its participants and less than 1% represented processes whose nature we could not identify
Summary
To better understand how complex biological systems work, we need to represent our knowledge in a clear and unambiguous form that is accessible to both scientists and computational agents. These representations form the basis for mathematical modelling and provides a prior-knowledge view for high-throughput data analysis, interpretation and hypothesis generation [16, 30]. Each language introduces a fixed set of glyphs (i.e. standardized symbols) that represent well-defined biological or bio-molecular elementary concepts (e.g. a macromolecule, a stoichiometric process, a stimulation). Such glyphs can be assembled to form complex SBGN diagrams. Similar higher order composite structures, often called templates,idioms or patterns appear in other formal modelling languages like circuit diagrams or UML as well as computer programming languages
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