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Endostatin is a C-terminal proteolytic fragment of collagen XVIII that is localized in vascular basement membrane zones in various organs, and inhibits angiogenesis and tumor growth. We have used protein and glycosaminoglycan arrays probed by surface plasmon resonance (SPR) to identify partners of endostatin, and to give further insights into its molecular mechanism of action. Glycosaminoglycans, matricellular proteins, collagens, the Abeta amyloid peptide, and transglutaminase-2 were found to bind endostatin. Endostatin was also shown to interact with intact pathogens (parasites invading the extracellular matrix) injected in buffer flow over SPR arrays, and could thus participate in host-pathogen interactions. The interaction network of endostatin was built using those experimental data and data available in the extracellular interaction database MatrixDB (http://matrixdb.ibcp.fr). The network was visualized with the software environment Cytoscape, and was annotated using UniProtKB, Gene Ontology and InterPro data. The predominant function associated with the endostatin network was cell adhesion. The most represented domains in the network were EGF (Epidermal Growth Factor) and EGF-like domains. 46% of endostatin partners bind calcium. Kinetics and affinity constants calculated by SPR experiments were integrated into the network to prioritize interactions according to their rate of formation and their stability. Data on binding sites were also integrated to discriminate simultaneous from mutually exclusive interactions. The integrated network was used as a framework to build a mathematical model of endostatin mechanism of action. We focus in the network established by endostatin at the cell surface, where it is able to bind to several receptors, to understand how endostatin selects a receptor and to determine if its binding to a receptor modify its interactions with other cell-surface associated molecules. The building of a dynamic interaction network will be helpful to understand how information/signaling is conveyed through the network and to predict the consequences of perturbations.