Literature DB >> 31199769

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

Adrien Rougny1,2, Vasundra Touré3, Stuart Moodie4, Irina Balaur5, Tobias Czauderna6, Hanna Borlinghaus7, Ugur Dogrusoz8,9, Alexander Mazein5,10,11, Andreas Dräger12,13,14, Michael L Blinov15, Alice Villéger16, Robin Haw17, Emek Demir18,19, Huaiyu Mi20, Anatoly Sorokin11, Falk Schreiber6,7, Augustin Luna21,22.   

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).

Entities:  

Keywords:  SBGN; biological network; circuit diagram; standard; systems biology; visualisation

Mesh:

Year:  2019        PMID: 31199769      PMCID: PMC6798820          DOI: 10.1515/jib-2019-0022

Source DB:  PubMed          Journal:  J Integr Bioinform        ISSN: 1613-4516


  16 in total

1.  Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology.

Authors:  Anna Niarakis; Dagmar Waltemath; James Glazier; Falk Schreiber; Sarah M Keating; David Nickerson; Claudine Chaouiya; Anne Siegel; Vincent Noël; Henning Hermjakob; Tomáš Helikar; Sylvain Soliman; Laurence Calzone
Journal:  Brief Bioinform       Date:  2022-07-18       Impact factor: 13.994

Review 2.  Computational models in systems biology: standards, dissemination, and best practices.

Authors:  Luis Sordo Vieira; Reinhard C Laubenbacher
Journal:  Curr Opin Biotechnol       Date:  2022-02-23       Impact factor: 10.279

3.  A detailed map of coupled circadian clock and cell cycle with qualitative dynamics validation.

Authors:  Adrien Rougny; Loïc Paulevé; Michèle Teboul; Franck Delaunay
Journal:  BMC Bioinformatics       Date:  2021-05-11       Impact factor: 3.169

4.  The status of causality in biological databases: data resources and data retrieval possibilities to support logical modeling.

Authors:  Vasundra Touré; Åsmund Flobak; Anna Niarakis; Steven Vercruysse; Martin Kuiper
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

Review 5.  Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.

Authors:  Tara Eicher; Garrett Kinnebrew; Andrew Patt; Kyle Spencer; Kevin Ying; Qin Ma; Raghu Machiraju; And Ewy A Mathé
Journal:  Metabolites       Date:  2020-05-15

Review 6.  Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019.

Authors:  Falk Schreiber; Björn Sommer; Gary D Bader; Padraig Gleeson; Martin Golebiewski; Michael Hucka; Sarah M Keating; Matthias König; Chris Myers; David Nickerson; Dagmar Waltemath
Journal:  J Integr Bioinform       Date:  2019-07-13

7.  RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis.

Authors:  Vidisha Singh; George D Kalliolias; Marek Ostaszewski; Maëva Veyssiere; Eleftherios Pilalis; Piotr Gawron; Alexander Mazein; Eric Bonnet; Elisabeth Petit-Teixeira; Anna Niarakis
Journal:  Database (Oxford)       Date:  2020-01-01       Impact factor: 3.451

8.  Pathway information extracted from 25 years of pathway figures.

Authors:  Kristina Hanspers; Anders Riutta; Martina Summer-Kutmon; Alexander R Pico
Journal:  Genome Biol       Date:  2020-11-09       Impact factor: 13.583

9.  Using Reactome to build an autophagy mechanism knowledgebase.

Authors:  Thawfeek Mohamed Varusai; Steven Jupe; Cristoffer Sevilla; Lisa Matthews; Marc Gillespie; Lincoln Stein; Guanming Wu; Peter D'Eustachio; Emmanouil Metzakopian; Henning Hermjakob
Journal:  Autophagy       Date:  2020-06-02       Impact factor: 16.016

10.  Visualizing metabolic network dynamics through time-series metabolomic data.

Authors:  Lea F Buchweitz; James T Yurkovich; Christoph Blessing; Veronika Kohler; Fabian Schwarzkopf; Zachary A King; Laurence Yang; Freyr Jóhannsson; Ólafur E Sigurjónsson; Óttar Rolfsson; Julian Heinrich; Andreas Dräger
Journal:  BMC Bioinformatics       Date:  2020-04-03       Impact factor: 3.169

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