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Nucleic Acids Res. 2019 Jan 8;47(D1):D376-D381. doi: 10.1093/nar/gky1035.

MatrixDB: integration of new data with a focus on glycosaminoglycan interactions.

Author information

1
Univ. Lyon, Institut de Chimie et Biochimie Moléculaires et Supramoléculaires (ICBMS), UMR 5246, University Lyon 1, CNRS, Villeurbanne F-69622, France.
2
Univ. Grenoble Alpes, CNRS, TIMC-IMAG / BCM, F-38000 Grenoble, France.
3
Department of Physiology and Biophysics, University of Illinois at Chicago, College of Medicine, Chicago, IL 60612, USA.
4
Centre de Recherches sur les Macromolécules Végétales (CERMAV), UPR 5301 CNRS, University Grenoble Alpes, Grenoble, 38041, France.

Abstract

MatrixDB (http://matrixdb.univ-lyon1.fr/) is an interaction database focused on biomolecular interactions established by extracellular matrix (ECM) proteins and glycosaminoglycans (GAGs). It is an active member of the International Molecular Exchange (IMEx) consortium (https://www.imexconsortium.org/). It has adopted the HUPO Proteomics Standards Initiative standards for annotating and exchanging interaction data, either at the MIMIx (The Minimum Information about a Molecular Interaction eXperiment) or IMEx level. The following items related to GAGs have been added in the updated version of MatrixDB: (i) cross-references of GAG sequences to the GlyTouCan database, (ii) representation of GAG sequences in different formats (IUPAC and GlycoCT) and as SNFG (Symbol Nomenclature For Glycans) images and (iii) the GAG Builder online tool to build 3D models of GAG sequences from GlycoCT codes. The database schema has been improved to represent n-ary experiments. Gene expression data, imported from Expression Atlas (https://www.ebi.ac.uk/gxa/home), quantitative ECM proteomic datasets (http://matrisomeproject.mit.edu/ecm-atlas), and a new visualization tool of the 3D structures of biomolecules, based on the PDB Component Library and LiteMol, have also been added. A new advanced query interface now allows users to mine MatrixDB data using combinations of criteria, in order to build specific interaction networks related to diseases, biological processes, molecular functions or publications.

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