Systems Biology Graphical Notation (SBGN); annotation; molecular network; ontology; template-based construction; visualisation; IRS1 protein, human; Insulin; Insulin Receptor Substrate Proteins; Protein Isoforms; Receptors, Somatomedin; Somatomedins; Mitogen-Activated Protein Kinases; Computer Graphics; Gene Expression Regulation; Gene Ontology; Humans; Insulin/genetics; Insulin/metabolism; Insulin Receptor Substrate Proteins/genetics; Insulin Receptor Substrate Proteins/metabolism; Mitogen-Activated Protein Kinases/genetics; Mitogen-Activated Protein Kinases/metabolism; Molecular Sequence Annotation; Protein Isoforms/genetics; Protein Isoforms/metabolism; Receptors, Somatomedin/genetics; Receptors, Somatomedin/metabolism; Signal Transduction; Somatomedins/genetics; Somatomedins/metabolism; Systems Biology/methods; Gene Regulatory Networks; Models, Biological; Software; Systems Biology; Information Systems; Molecular Biology
Abstract :
[en] A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the Bricks Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.
Disciplines :
Biotechnology
Author, co-author :
Rougny, Adrien; Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Aomi, Tokyo, Japan ; The Donnelly Centre, University of Toronto, M5S 3E1, Toronto, Canada ; Com. Bio Big Data Open Innovation Lab. (CBBD-OIL), AIST, Aomi, Tokyo, Japan
Touré, Vasundra; Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Realfagbygget, 7491 Trondheim, Norway
Albanese, John; R. D. Berlin Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, Farmington, CT 06030, USA
Waltemath, Dagmar; Medical Informatics Laboratory, Institute for Community Medicine, University Medicine Greifswald, D-17475 Greifswald, Germany
Shirshov, Denis; European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007 Lyon, France ; Institute of Cell Biophysics, Russian Academy of Sciences, 3 Institutskaya Street, Pushchino, Moscow Region, 142290, Russia
Sorokin, Anatoly; Institute of Cell Biophysics, Russian Academy of Sciences, 3 Institutskaya Street, Pushchino, Moscow Region, 142290, Russia ; Moscow Institute of Physics and Technology, 9 Institutsky per., Dolgoprudny, Moscow Region, 141700, Russia ; University of Liverpool, Liverpool L7 3EA, UK
Bader, Gary D; The Donnelly Centre, University of Toronto, M5S 3E1, Toronto, Canada
Blinov, Michael L; R. D. Berlin Center for Cell Analysis and Modeling, University of Connecticut School of Medicine, Farmington, CT 06030, USA ; The Donnelly Centre, University of Toronto, M5S 3E1, Toronto, Canada
MAZEIN, Alexander ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core ; European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007 Lyon, France ; Institute of Cell Biophysics, Russian Academy of Sciences, 3 Institutskaya Street, Pushchino, Moscow Region, 142290, Russia
External co-authors :
yes
Language :
English
Title :
SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks.
Ashburner M. Catherine A Ball, Judith A Blake, David Botstein, Heather Butler, J Michael Cherry, Allan P Davis, Kara Dolinski, Selina S Dwight, Janan T Eppig, et al.Gene ontology: Tool for the unification of biology. Nat Genet 2000; 25(1): 25 9.
Balaur I, Roy L, Mazein A, et al. cd2sbgnml: bidirectional conversion between celldesigner and sbgn formats. Bioinformatics 2020; 36(8): 2620 2.
Bergmann FT, Czauderna T, Dogrusoz U, et al. Systems biology graphical notation markup language (sbgnml) version 0.3. J Integr Bioinform 1(ahead-of-print)2020.
Chelliah V, Juty N, Ajmera I, et al. Biomodels: Ten-year anniversary. Nucleic Acids Res 2015; 43(D1): D542 8.
Gene Ontology Consortium. The gene ontology resource: 20 years and still going strong. Nucleic Acids Res 2019; 47(D1): D330 8.
Courtot M, Juty N, Knöpfer C, et al. Controlled vocabularies and semantics in systems biology. Mol Sys Biol 2011; 7(1): 543.
Ann E Cowan, Pedro Mendes, and Michael L Blinov. Modelbricks modules for reproducible modeling improving model annotation and provenance. NPJ Systems Biology and Applications, 5(1): 1 6, 2019.
Czauderna T, Klukas C, Schreiber F. Editing, validating and translating of sbgn maps. Bioinformatics 2010; 26(18): 2340 1.
Demir E. Michael P Cary, Suzanne Paley, ken Fukuda, Christian Lemer, Imre Vastrik, Guanming Wu, Peter D eustachio, Carl Schaefer, Joanne Luciano, et al.The biopax community standard for pathway data sharing. Nat Biotechnol 2010; 28(9): 935 42.
Fabregat A, Jupe S, Matthews L, et al. The reactome pathway knowledgebase. Nucleic Acids Res 2018; 46(D1): D649 55.
Funahashi A,Matsuoka Y, Jouraku A, et al. Celldesigner 3.5: A versatile modeling tool for biochemical networks. Proc IEEE 2008; 96(8): 1254 65.
Henkel R, Wolkenhauer O, Waltemath D. Combining computational models, semantic annotations and simulation experiments in a graph database. Database 2015; 2015.
Michael Hucka, Frank T Bergmann, Andreas Dräger, Stefan Hoops, Sarah M Keating, Nicolas Le Novère, Chris J Myers, Brett G Olivier, Sven Sahle, James C Schaff, et al. The systems biology markup language (sbml): language specification for level 3 version 2 core. J Integr Bioinform, 15(1), 2018.
Hucka M, Finney A. Herbert M Sauro, Hamid Bolouri, John C Doyle, Hiroaki Kitano, Adam P Arkin, Benjamin J Bornstein, Dennis bray, Athel Cornish-Bowden, et al.The systems biology markup language (sbml): A medium for representation and exchange of biochemical network models. Bioinformatics 2003; 19(4): 524 31.
Junker A, Sorokin A, Czauderna T, et al. Wiring diagrams in biology: Towards the standardized representation of biological information. Trends Biotechnol 2012; 30(11): 555 7.
Kitano H, Funahashi A, Matsuoka Y, et al. Using process diagrams for the graphical representation of biological networks. Nat Biotechnol 2005; 23(8): 961 6.
Inna Kuperstein, E Bonnet, Hien-Anh Nguyen, David Cohen, Eric Viara, Luca Grieco, S Fourquet, Laurence calzone, Christophe Russo, Maria Kondratova, et al. atlas of cancer signalling network: A systems biology resource for integrative analysis of cancer data with google maps. Oncogenesis, 4(7): e160 e160, 2015.
Kutmon M, van Iersel MP, Bohler A, et al. Pathvisio 3: An extendable pathway analysis toolbox. PLoS Comput Biol. In: 11(2):e1004085, 2015.
Lambusch F, Waltemath D, Wolkenhauer O, et al. Identifying frequent patterns in biochemical reaction networks: A workf low. Database 2018; 2018.
Lamy J-B. Owlready: ontology-oriented programming in python with automatic classification and high level constructs for biomedical ontologies. Artif IntellMed 2017; 80:11 28.
Le Novere, Hucka M, Mi H, et al. Mirit I Aladjem, Sarala M Wimalaratne, et al.The systems biology graphical notation. Nat Biotechnol 2009; 27(8): 735 41.
Mi H, Dong Q, Muruganujan A, et al. Panther version 7: improved phylogenetic trees, orthologs and collaboration with the gene ontology consortium. Nucleic Acids Res 2010; 38(suppl_1): D204 10.
Mi H, Schreiber F, Moodie S, et al. Systems biology graphical notation: Activity f low language level 1 version 1. J Integr Bioinform 2015; 12(2): 340 81.
Mark A. Musen. The protégé project: A look back and a look forward. AI matters 2015; 1(4): 4 12.
Rougny A. Sbgntikz a ti k z library to draw sbgn maps. Bioinformatics 2019; 35(21): 4499 500.
Rougny A, Touré V,Moodie S, et al. Systems biology graphical notation: process description language level 1 version 2.0. J Integr Bioinform 2019; 16(2).
Sari M, Bahceci I, Dogrusoz U, et al. Sbgnviz: A tool for visualization and complexity management of sbgn process description maps. PloS One 2015; 10(6): e0128985.
Sarwar DM, Kalbasi R, Gennari JH, et al. Model annotation and discovery with the physiome model repository. BMC Bioinformatics 2019; 20(1): 1 10.
SiebenhallerM,Nielsen SS, McGee F, et al. Human-like layout algorithms for signalling hypergraphs: outlining requirements. Brief Bioinform 2020; 21(1): 62 72.
Sompairac N, Modamio J, Barillot E, et al. Metabolic and signalling network maps integration: Application to cross-Talk studies and omics data analysis in cancer.BMC Bioinformatics 2019; 20(4): 140.
Sorokin A, Le Novère, Luna A, et al. Systems biology graphical notation: entity relationship language level 1 version 2. J Integr Bioinform 2015; 12(2): 281 339.
Thomas PD,CampbellMJ,Kejariwal A, et al. Panther: A library of protein families and subfamilies indexed by function. Genome Res 2003; 13(9): 2129 41.
Touré V, Mazein A, Waltemath D, et al. Ston: exploring biological pathways using the sbgn standard and graph databases. BMC Bioinformatics 2016; 17(1): 1 9.
Touré V, Dräger A, Luna A, et al. The systems biology graphical notation: Current status and applications in systems medicine. In: In Reference Module in Biomedical Sciences. Elsevier, 2020.
van Martijn P. Iersel, Thomas Kelder, Alexander R Pico, Kristina Hanspers, Susan Coort, Bruce R Conklin, and Chris Evelo. Presenting and exploring biological pathways with pathvisio. BMC bioinformatics 2008; 9(1): 1 9.
Torsten Vogt, Tobias Czauderna, and Falk Schreiber. Translation of sbgn maps: process description to activity f low. BMC Sys Biol, 7(1):115, 2013.
