Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3

• Published in: Journal of integrative bioinformatics Vol. 12; no. 2; pp. 213 - 280
• Main Authors: Moodie, Stuart, Le Novère, Nicolas, Demir, Emek, Mi, Huaiyu, Villéger, Alice
• Format: Journal Article
• Language: English
• Published: Germany IMBio e.V 04.09.2015
• Subjects: Animals; Biological Ontologies; Computer Graphics - standards; Datasets as Topic - standards; Documentation - standards; Guidelines as Topic - standards; Humans; Information Storage and Retrieval - standards; Internationality; Models, Biological; Programming Languages; Proteome - metabolism; Signal Transduction - physiology; Systems Biology - standards
• ISSN: 1613-4516
• DOI: 10.2390/biecoll-jib-2015-263

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 Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.