Introduction
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 as: providing consistent syntax and unambiguous semantics of your
visual representation [3, 4]; improving shareability, reusability, and reproducibility
of your network [2]; and enabling conversion of a visual network into an executable
mathematical model [5].
The creation of expressive and impactful SBGN maps requires some exercise. In the
following, we share our experiences with creating SBGN maps. We offer guidelines and
hints to scientists who wish to beautify and export their biological networks in SBGN.
When reading the tips, please keep in mind that SBGN is a flexible standard. The provided
tips should be considered as recommendations—your map will not be wrong if you do
not follow them, but hopefully it will gain more impact.
Guidelines
Tip 1. Know the message your network should convey
The scientific question you want to address should be clear, as should the message
you want to communicate to the reader. Specifying your message will help you choose
what to omit, what to represent, and how to represent it. For example, when representing
a network, you should think about the type of pathway you want to model: Do you want
to say that phosphoinositide 3-Kinase (PI3K) activates protein kinase B (AKT, signaling
information), or do you want to say that PI3K transforms phosphatidylinositol 4,5-bisphosphate
(PIP2) into phosphatidylinositol (3,4,5)-trisphosphate (PIP3) and that PIP3 binds
to AKT (metabolic information)? The understanding of the network’s biochemical and
biophysical organisation will help you structure the map, and SBGN helps you to sketch
it out.
Tip 2. Know your audience
Keep your target audience in mind: different readers perceive different messages and
focus on different aspects of a network. For example, a biochemist will generally
be interested in a detailed map highlighting biological entities (e.g., macromolecules
depicted in an SBGN PD map) and their interactions; whereas a cancer researcher will
be concerned about mechanisms and feedback loops that occur in a specific cell type
(depicted in SBGN AF notation). To ensure the successful transmission of your message,
identify your audience and adapt the network's representation accordingly. Ask yourself:
What do they know and what do they not know? What are they interested in? This will
lead you to determine the most appropriate level of representation to visualise your
network.
Tip 3. Choose the right SBGN language
Design your map in a reasonable level of detail. Fig 1 shows one biological system
represented with glyphs from the three SBGN languages. In SBGN PD, we represent the
fact that the depolarisation of the membrane triggers the opening of the sodium ion
(Na+) channel, which enables the import of Na+ from the extracellular space to the
cytoplasm. In SBGN ER, the depolarisation stimulates the assignment of value “true”
to the state “open” of the Na+ channel, necessary to stimulate the relocation of Na+
into the cytoplasm. In SBGN AF, a cascade of signals is shown where the depolarisation
stimulates the activity of Na+ channels, which in turn, is necessary to stimulate
the activity of Na+ in the cytoplasm. For more details about the symbols used, please
refer to the SBGN reference cards (http://sbgn.github.io/sbgn/templates). Deciding
what knowledge to transport through your map will guide you in choosing the right
SBGN flavour.
10.1371/journal.pcbi.1005740.g001
Fig 1
Three different SBGN representations of Na+ transport into the cytoplasm by voltage-dependant
channels.
(a), The depolarisation (“perturbation” symbol) of the membrane triggers (“stimulation”
symbol, arrow with white head) the opening of the Na+ channel, which enables the import
of Na+ from the extracellular space to the cytoplasm. Each sodium channel glyph contains
a “unit of information” glyph (rectangle at the top left) that gives information about
the conformational state of the channel. (b), The depolarisation stimulates the assignment
of value “true” to the state “open” of the Na+ channel. This value is necessary to
stimulate (“necessary stimulation” symbol, arrow with white head and a vertical line)
the relocation of Na+ into the cytoplasm. (c), A cascade of signals is represented
where the depolarisation stimulates the activity of Na+ channels, which in turn, is
necessary to stimulate the activity of Na+ in the cytoplasm. Na+, sodium ion; SBGN,
Systems Biology Graphical Notation.
Tip 4. Define components and interactions in the network
List the reactions constituting your network and carefully choose the names of the
biological components that will be displayed as labels in the SBGN nodes. The suitable
SBGN glyph to represent a biological component can be chosen by using either the reference
cards (http://sbgn.github.io/sbgn/templates), the information provided by your SBGN-compliant
software, or the information given in the language specifications. For example, if
your component is a protein, you may use the SBGN macromolecule glyph depicted on
the reference card for SBGN PD. Once your biological components are mapped on SBGN
glyphs, you should choose appropriate arcs to link the components together and build
the connectivity of your network.
Tip 5. Select the right level of granularity for your map
A network can be visualised at different levels of detail, as exemplified in Fig 2.
10.1371/journal.pcbi.1005740.g002
Fig 2
Representation of energy storage by the ATP synthase at different levels of detail
from the more abstract layer (left) to the more detailed layer (right).
In the first diagram, the nature of the entities is unspecified (oval shaped glyphs)
and the modulation is of unknown direction. The second diagram is more detailed with
a macromolecule “ATP synthase” that stimulates the reaction consuming the simple chemicals
“ADP” and “Pi” to produce the simple chemical “ATP.” In the third diagram, the ATP
glyph has been substituted by a complex, making the diagram even more precise. Finally,
the forth diagram highlights an identified complex catalysing the synthesis of a simple
chemical. ADP, adenosine diphosphate; Pi, inorganic phosphate.
The SBGN does not tell you how to represent a system, but tells your readers how to
interpret what you have drawn. It is important to be as specific as you can be about
the encoded biology without diluting your message. In particular, omitted information
might make it hard for others to interpret your network and hence, to understand your
message. At the same time, the right level of abstraction must be chosen for the important
parts of your network to stand out to the readers.
Tip 6. Design your SBGN map
A careful design of your SBGN map could provide additional biological information
on top of your network. Start by creating the components and their interactions (as
mentioned in Tip 4), then add necessary information in respect to Tip 5.
A good layout improves the readability of your network and can also speed up interpretation,
in particular if you followed Tip 2. For instance, people working on signaling pathways
generally put the plasma membrane on the top of a map and the nucleus on the bottom,
with the main flow of information going downward. You can either apply an automatic
layout provided by the software tool, or create the layout manually. A manual layout
may be time-consuming, but the result will highlight your message better (Tip 1).
Often, a combination of a an automatic layout with a manual enhancement leads to the
most satisfying results.
Tip 7. Beautify your SBGN map
Our eye catches and our brain focuses on things we find attractive. Therefore, your
map should be visually appealing to your audience if you expect others to look into
the details of your work. Although such graphical characteristics are neither covered
nor regulated by the SBGN, add carefully chosen colors, adapt the label fonts and
the size of the symbol to the components, and keep arc lengths short, etc. To limit
the number of crossing arcs, make use of clone markers to duplicate “hub nodes.” This
will help break up the pathway and clear the visualisation, as shown in Fig 3. Beautify
your network so people want to look at it!
10.1371/journal.pcbi.1005740.g003
Fig 3
Example of the Drosophila cell cycle initial SBGN drawing (left) and beautified SBGN
network (right).
We generated the SBGN map of the following study “Dynamical modeling of syncytial
mitotic cycles in Drosophila embryos” by Calzone et al. [16, 17]. First, we created
an initial map with the different reactions found in the Drosophila cell cycle. Then
we beautified the map by duplicating FZY with clone markers in order to reduce edge
crossings, adding colors, and optimising arc positions. The colors categorise the
different reactions: green processes represent creation or degradation of entities
(“source and sink”) and grey processes show import and export of entities between
compartments. The red processes and arcs visualise the positive feedback exerted by
the MPF. The purple processes highlight the switch between the activation and the
inactivation of MPF. FZY, fizzy; MPF, maturation promoting factor; SBGN, Systems Biology
Graphical Notation.
Tip 8. Manage your SBGN map and its content
When satisfied with the map you designed, save it in different formats. To be able
to edit the map in the future, save it in the richest source format recognised by
the software (e.g., Inkscape Scalable Vector Graphics (SVG) for Inkscape, or SBML
with CellDesigner extension for CellDesigner). To ensure that your readers can view
your map as you designed it, a raster file format (an image made up of pixels) such
as Portable Network Graphics (PNG) is probably the best, or a vector format such as
Portable Document Format (PDF) for a zoomable image. Finally, save the formal representation
of your map in the SBGN Markup Language (SBGN-ML) format to increase compatibility
between editor and viewer software (see S1 Supporting information for the SBGN-ML
files of the figures). SBGN-ML is an Extensible Markup Language (XML)-based format
specifically designed to store and exchange SBGN maps [3]. By providing your map in
several formats, your work will be shareable and reusable by machines and by humans.
Tip 9. Link the original data to your SBGN map
When publishing your data, provide the SBGN visualisations saved in formats as described
in Tip 8, and link them to your original data, whether the data is a model, a publication,
a data set, or other. It will benefit your work and help the readers to understand
your network. You can, for instance, build a Computational Modeling in Biology Network
(COMBINE) archive, a container format that facilitates the sharing and reproducibility
of Systems Biology projects [14]. By using the web-based CombineArchive tool [15],
you can easily and quickly create a COMBINE archive by uploading and packing all files
relevant to the study, among which the newly generated SBGN file.
Tip 10. Seek help from the SBGN community
The SBGN editorial board provides and maintains guidelines, tutorials, and examples
on their homepage (see S1 Table for a list of useful links). Feedback can be requested
and questions can be asked on the SBGN mailing lists for end-users and developers
(http://sbgn.github.io/sbgn/contact). The SBGN community is an extremely diverse and
well-established community of computational biologists, modelers, computer scientists,
and scientists from related fields. There will always be people willing to help, and
questions are in general answered quickly. Remember, if you asked yourself a question,
someone probably wondered the same before, so don’t be shy!
Conclusions
A structured, standardised, and eye-catching map tremendously improves the readability
and the reusability of your work. Communication will be more effective and your message
will be passed successfully. Please consider providing your next network in SBGN!
Supporting information
S1 Table
SBGN online resources.
This table provides a list of links that are useful for working with the SBGN standard.
SBGN, Systems Biology Graphical Notation.
(XLSX)
Click here for additional data file.
S1 Supporting information
Compressed SBGN-ML documents.
This compressed zip file contains the SBGN-ML documents generated for the three figures
presented in the quick tips. SBGN-ML, Systems Biology Graphical Notation Markup Language.
(ZIP)
Click here for additional data file.