Researchers at the California Institute of Technology (Caltech) and their colleagues in 30 laboratories worldwide have released a new set of standards for graphically representing biological information—the biology equivalent of the circuit diagram in electronics. This visual language should make it easier to exchange complex information, so that biological models are depicted more accurately, consistently, and in a more readily understandable way.
The new standard, called the Systems Biology Graphical Notation (SBGN), was published in the August 8 issue of the journal Nature Biotechnology.
Researchers use standardized visual languages to communicate complex information in many scientific and engineering fields. A well-known example is the circuit diagram in electrical engineering. However, until now, biology lacked a standardized notation for describing biological interactions, pathways, and networks, even though the discipline is dominated by graphical information.
The SBGN project was launched in 2005 as a united effort to specifically develop a new graphical standard for molecular and systems-biology applications. The project, which was initiated by Hiroaki Kitano of the Systems Biology Institute in Tokyo, Japan, is coordinated by Nicolas Le Novère of the European Molecular Biology Laboratory’s European Bioinformatics Institute in Cambridge, England, and senior research fellow Michael Hucka, codirector of the Biological Network Modeling Center at Caltech’s Beckman Institute. The international team of researchers that created SBGN is composed of biochemists, modelers, and computer scientists, who developed the notation in collaboration with a broader community of researchers constituting the target user community.
“Engineers, architects, physicists, and software developers all have standard graphical notations for depicting the things they work on, which makes it possible for everyone in those fields to be on the same page, as it were,” says Hucka. “I think SBGN represents the first truly broad-based attempt at establishing the same kind of standardization in biology.”
SBGN will make it easier for biologists to understand each other’s models and share network diagrams more easily, which, Hucka says, has never been more important than in today’s era of high-throughput technologies and large-scale network reconstruction efforts. A standard graphical notation will help researchers share this mass of data more efficiently and accurately, which will benefit systems biologists working on a variety of biochemical processes, including gene regulation, metabolism, and cellular signaling.
“Finally, and perhaps most excitingly,” adds Hucka, “I believe that, just as happened with the engineering fields, SBGN will act as an enabler for the emergence of new industries devoted to the creation of software tools for working with SBGN, as well as its teaching and publication.”
Previous graphical notations in biology have tended to be ambiguous, used in different ways by different researchers, and only suited to specific needs—for example, to represent metabolic networks or signaling pathways. Past efforts to create a more rigid notation failed to become accepted as a standard by the community. Hucka and his collaborators believe that SBGN should be more successful because it represents a more concerted effort to establish a standard by engaging many biologists, modelers, and software-tool developers. In fact, many of those involved in the SBGN effort are the same pioneers who proposed previous notations, demonstrating the degree to which they endorse SBGN as a new standard.
To ensure that this new visual language does not become too vast and complicated, the researchers decided to define three separate types of diagram, which describe molecular process, relationships between entities, and links among biochemical activities. These different types of diagrams complement each other by representing different “views” of the same information, presented in different ways for different purposes, but reusing most of the same graphical symbols. This approach reduces the complexity of any one type of diagram while broadening the range of what can be expressed about a given biological system.
“As biology focuses more on managing complexity with quantitative and systematic methods, standards such as SBGN play an essential role. SBGN combines an intuitive notation with the rigorous style of engineering and math,” says John Doyle, the John G. Braun Professor of Control and Dynamical Systems, Bioengineering, and Electrical Engineering at Caltech.
“As with SBML (the Systems Biology Markup Language), Mike and his collaborators have provided the kind of solid foundation that the whole community can build on. SBML has been a highly successful standardization effort for software interoperability, and SBGN is sure to have the same kind of impact on human communication in biology,” Doyle add