ScienceDaily (Aug. 12, 2009) — 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.
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Graphic showing the catalysis of ERK (extracellular signal-regulated kinase) phosphorylation by the kinase MEK in the growth factors signalling pathway. This is illustrated by the three SBGN diagrams: process, entity relationship and activity flow. (Credit: Copyright EMBL)
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.
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Perspective abstract
Nature Biotechnology 27, 735 - 741 (2009)
Published online: 7 August 2009 | doi:10.1038/nbt.1558
The Systems Biology Graphical Notation
Nicolas Le Novère1, Michael Hucka2, Huaiyu Mi3, Stuart Moodie4, Falk Schreiber5,6, Anatoly Sorokin7, Emek Demir8, Katja Wegner9, Mirit I Aladjem10, Sarala M Wimalaratne11, Frank T Bergman12, Ralph Gauges13, Peter Ghazal4,14, Hideya Kawaji15, Lu Li1, Yukiko Matsuoka16, Alice Villéger17,18, Sarah E Boyd19, Laurence Calzone20, Melanie Courtot21, Ugur Dogrusoz22, Tom C Freeman14,23, Akira Funahashi24, Samik Ghosh16, Akiya Jouraku24, Sohyoung Kim10, Fedor Kolpakov25,26, Augustin Luna10, Sven Sahle13, Esther Schmidt1, Steven Watterson4,22, Guanming Wu27, Igor Goryanin4, Douglas B Kell18,28, Chris Sander8, Herbert Sauro12, Jacky L Snoep29, Kurt Kohn10 & Hiroaki Kitano16,30,31
Abstract
Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.
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EMBL European Bioinformatics Institute, Hinxton, UK.
Engineering and Applied Science, California Institute of Technology, Pasadena, California, USA.
SRI International, Menlo Park, California, USA.
Centre for Systems Biology at Edinburgh, University of Edinburgh, Edinburgh, UK.
Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.
Institute of Computer Science, University of Halle, Halle, Germany.
School of Informatics, University of Edinburgh, Edinburgh, UK.
Memorial Sloan Kettering Cancer Center - Computational Biology Center, New York, NY, USA.
Science and Technology Research Institute, University of Hertfordshire, Hatfield, UK.
National Cancer Institute, Bethesda, Maryland, USA.
Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Department of Bioengineering, University of Washington, Seattle, Washington, USA.
BIOQUANT, University of Heidelberg, Heidelberg, Germany.
Division of Pathway Medicine, University of Edinburgh Medical School, Edinburgh, UK.
Riken OMICS Science Center, Yokohama City, Kanagawa, Japan.
The Systems Biology Institute, Tokyo, Japan.
School of Computer Science, University of Manchester, Manchester, UK.
Manchester Interdisciplinary Biocentre, Manchester, UK.
Clayton School of Information Technology, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
U900 INSERM, Paris Mines Tech, Institut Curie, Paris, France.
Terry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, British Columbia, Canada.
Bilkent Center for Bioinformatics, Bilkent University, Ankara, Turkey.
The Roslin Institute, University of Edinburgh, Midlothian, UK.
Department of Biosciences and Informatics, Keio University, Hiyoshi, Kouhoku-ku, Yokohama, Japan.
Institute of Systems Biology, Novosibirsk, Russia.
Design Technological Institute of Digital Techniques SB RAS, Novosibirsk, Russia.
Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
School of Chemistry, University of Manchester, Manchester, UK.
Department of Biochemistry, Stellenbosch University, Matieland, South Africa.
Sony Computer Science Laboratories, Tokyo, Japan.
Okinawa Institute of Science and Technology, Okinawa, Japan.
Correspondence to: Nicolas Le Novère1 e-mail: lenov@ebi.ac.uk.
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