Details

Autor(en) / Beteiligte

• Wu, Guanming
• Mi, Huaiyu
• Kim, Sohyoung
• Luna, Augustin
• Sorokin, Anatoly
• Jouraku, Akiya
• Li, Lu
• Wimalaratne, Sarala M
• Wegner, Katja
• Watterson, Steven
• Bergman, Frank T
• Villéger, Alice
• Kawaji, Hideya
• Sahle, Sven
• Ghosh, Samik
• Schreiber, Falk
• Demir, Emek
• Kohn, Kurt
• Funahashi, Akira
• Kolpakov, Fedor
• Sander, Chris
• Kitano, Hiroaki
• Schmidt, Esther
• Sauro, Herbert
• Goryanin, Igor
• Kell, Douglas B
• Ghazal, Peter
• Aladjem, Mirit I
• Novère, Nicolas Le
• Moodie, Stuart
• Calzone, Laurence
• Matsuoka, Yukiko
• Courtot, Melanie
• Freeman, Tom C
• Snoep, Jacky L
• Boyd, Sarah E
• Hucka, Michael
• Gauges, Ralph
• Dogrusoz, Ugur

Titel

The Systems Biology Graphical Notation

Ist Teil von

• Nature biotechnology, 2009-08, Vol.27 (8), p.735-741

Ort / Verlag

New York: Nature Publishing Group US

Erscheinungsjahr

2009

Quelle

MEDLINE

Beschreibungen/Notizen

• A group of scientists in the systems biology community propose visual conventions for drawing biological diagrams. 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.