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

被引:19
|
作者
Sorokin, Anatoly [1 ]
Le Novere, Nicolas [2 ]
Luna, Augustin [3 ]
Czauderna, Tobias [4 ]
Demir, Emek [3 ]
Haw, Robin [5 ]
Mi, Huaiyu [6 ]
Moodie, Stuart [4 ,7 ]
Schreiber, Falk [8 ]
Villeger, Alice [9 ]
机构
[1] Inst Cell Biophys RAS, Pushchino, Moscow Region, Russia
[2] Babraham Inst, Babraham, Cambs, England
[3] Mem Sloan Kettering Canc Ctr, New York, NY USA
[4] Monash Univ, Clayton, Vic 3800, Australia
[5] Ontario Inst Canc Res, Toronto, ON, Canada
[6] Univ Southern Calif, Los Angeles, CA 90089 USA
[7] Eight Pillars Ltd, Edinburgh, Midlothian, Scotland
[8] MLU Halle, Halle, Saale, Germany
[9] Freelance IT Consultant, London, England
来源
JOURNAL OF INTEGRATIVE BIOINFORMATICS | 2015年 / 12卷 / 02期
基金
英国生物技术与生命科学研究理事会;
关键词
D O I
10.2390/biecoll-jib-2015-264
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:59
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