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
Résumé :
[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 :
Biotechnologie
Auteur, co-auteur :
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
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks.
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