Quick tips for creating effective and impactful biological pathways using the Systems Biology Graphical Notation

With the rise of Systems Biology, the research focus moved from studying a single biological object to studying an ensemble of objects in interaction. This ensemble can be described as a network delineating the biological aspects of a data item or as a map visually representing the network’s structure and behaviour [1]. Maps have proven useful to understand biological networks, and they are frequently drawn to visually support scientific facts in presentations and journal publications. Visual representations of biological facts thus play an important role in science communication, particularly for the interdisciplinary dialogue between experimental and theoretical groups. The comprehension of such maps in a journal publication relies either on lengthy legends or, more often, on the reader’s interpretation. This interpretation is largely based on context, prior knowledge, and assumptions about the intentions of the map designer. Common symbols help to unambiguously communicate facts. The Systems Biology Graphical Notation (SBGN, [2]) is an international, established, and widely used standard to reduce the ambiguity in representations of biological maps. The community standard provides sets of well-defined symbols, each of them with a specific biological meaning. For example, a round-corner rectangle in an SBGN map represents a macromolecule. The SBGN offers the following three complementary languages to visually describe the biology: SBGN Process Descriptions (SBGN PD [11]), SBGN Entity Relationships (SBGN ER [12]), and SBGN Activity Flows (SBGN AF [13]). Metabolic maps depicting detailed biochemical reactions, state transitions, and transport are best represented with SBGN PD. Nonmechanistic influences between biological entities, such as signaling pathways and regulatory networks, are best highlighted in SBGN AF. Finally, SBGN ER visualises independent interactions between biological entities without any temporal aspect. Maps in SBGN ER are therefore useful to avoid combinatorial explosions resulting from multicomponent complexes and molecules with multiple states. SBGN is supported by a range of visualisation tools, including CellDesigner [5], SBGN-Editor (SBGN-ED) [6], PathVisio [7] and SBGNViz [8]. SBGN diagrams are published in open repositories such as BioModels [9] (for computational models) and Reactome [10] (for pathway data). To help scientists understand SBGN maps, the SBGN community provides detailed specification documents, software libraries [3], and online learning materials (http://sbgn. github.io/sbgn/). The benefits of having a network represented in SBGN can be summarised