Systems biology graphical notation markup language (SBGNML) version 0.3.

SBGN biological process diagrams network biology; pathway diagram systems biology visualization

Journal

Journal of integrative bioinformatics
ISSN: 1613-4516
Titre abrégé: J Integr Bioinform
Pays: Germany
ID NLM: 101503361

Informations de publication

Date de publication:
22 Jun 2020
Historique:
received: 01 04 2020
accepted: 16 04 2020
pubmed: 23 6 2020
medline: 28 4 2021
entrez: 23 6 2020
Statut: epublish

Résumé

This document defines Version 0.3 Markup Language (ML) support for the Systems Biology Graphical Notation (SBGN), a set of three complementary visual languages developed for biochemists, modelers, and computer scientists. SBGN aims at representing networks of biochemical interactions in a standard, unambiguous way to 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. SBGN is defined neutrally to programming languages and software encoding; however, it is oriented primarily towards allowing models to be encoded using XML, the eXtensible Markup Language. The notable changes from the previous version include the addition of attributes for better specify metadata about maps, as well as support for multiple maps, sub-maps, colors, and annotations. These changes enable a more efficient exchange of data to other commonly used systems biology formats (e. g., BioPAX and SBML) and between tools supporting SBGN (e. g., CellDesigner, Newt, Krayon, SBGN-ED, STON, cd2sbgnml, and MINERVA). More details on SBGN and related software are available at http://sbgn.org. With this effort, we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner.

Identifiants

pubmed: 32568733
doi: 10.1515/jib-2020-0016
pii: jib-2020-0016
pmc: PMC7756621
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIGMS NIH HHS
ID : P41 GM103504
Pays : United States
Organisme : NHGRI NIH HHS
ID : U41 HG006623
Pays : United States

Auteurs

Frank T Bergmann (FT)

BioQUANT/COS, Heidelberg University, INF 267, Heidelberg, 69120, Germany.

Tobias Czauderna (T)

Faculty of Information Technology, Monash University, Melbourne, Australia.

Ugur Dogrusoz (U)

Computer Engineering Department, Bilkent University, Ankara, 06800, Turkey.
i-Vis Research Lab, Bilkent University, Ankara, 06800, Turkey.

Adrien Rougny (A)

Biotechnology Research Institute for Drug Discovery, AIST, Tokyo, 135-0064, Japan.
Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), AIST, Tokyo, 169-8555, Japan.

Andreas Dräger (A)

Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), Tübingen, 72076, Germany.
Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany.
German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, 72076, Germany.

Vasundra Touré (V)

Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Alexander Mazein (A)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, L-4367, Luxembourg.
European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, Lyon, 69007, France.

Michael L Blinov (ML)

Center for Cell Analysis and Modeling, UConn Health, Farmington, CT, 06030, USA.

Augustin Luna (A)

cBio Center, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA.

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