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Systems Biology Graphical Notation: Process Description language Level 1 Version 2.0

Authors :
Rougny Adrien
Touré Vasundra
Moodie Stuart
Balaur Irina
Czauderna Tobias
Borlinghaus Hanna
Dogrusoz Ugur
Mazein Alexander
Dräger Andreas
Blinov Michael L.
Villéger Alice
Haw Robin
Demir Emek
Mi Huaiyu
Sorokin Anatoly
Schreiber Falk
Luna Augustin
Source :
Journal of Integrative Bioinformatics, Vol 16, Iss 2 (2019)
Publication Year :
2019
Publisher :
De Gruyter, 2019.

Abstract

The Systems Biology Graphical Notation (SBGN) is an international community effort that aims to standardise the visualisation of pathways and networks for readers with diverse scientific backgrounds as well as to support an efficient and accurate exchange of biological knowledge between disparate research communities, industry, and other players in systems biology. SBGN comprises the three languages Entity Relationship, Activity Flow, and Process Description (PD) to cover biological and biochemical systems at distinct levels of detail. PD is closest to metabolic and regulatory pathways found in biological literature and textbooks. Its well-defined semantics offer a superior precision in expressing biological knowledge. PD represents mechanistic and temporal dependencies of biological interactions and transformations as a graph. Its different types of nodes include entity pools (e.g. metabolites, proteins, genes and complexes) and processes (e.g. reactions, associations and influences). The edges describe relationships between the nodes (e.g. consumption, production, stimulation and inhibition). This document details Level 1 Version 2.0 of the PD specification, including several improvements, in particular: 1) the addition of the equivalence operator, subunit, and annotation glyphs, 2) modification to the usage of submaps, and 3) updates to clarify the use of various glyphs (i.e. multimer, empty set, and state variable).

Details

Language :
English
ISSN :
16134516
Volume :
16
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Journal of Integrative Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.7dccc9b7f8db45aea9669c8e70d429b8
Document Type :
article
Full Text :
https://doi.org/10.1515/jib-2019-0022