Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to su...

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Published inJournal of integrative bioinformatics Vol. 12; no. 2; pp. 281 - 339
Main Authors Sorokin, Anatoly, Le Novère, Nicolas, Luna, Augustin, Czauderna, Tobias, Demir, Emek, Haw, Robin, Mi, Huaiyu, Moodie, Stuart, Schreiber, Falk, Villéger, Alice
Format Journal Article
LanguageEnglish
Published Germany De Gruyter 01.06.2015
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Summary:The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.
ISSN:1613-4516
1613-4516
DOI:10.1515/jib-2015-264