Angiogenesis plays a key role in several diseases including cancer, ischemic vascular disease, and Alzheimer’s disease. chemical genetic screening of endothelial tube formation provides a robust approach for identifying signalling components that impact microvascular network morphology as well as endothelial cell biology. However, the analysis of the resulting imaging datasets has been limited to a few phenotypic features such as the total tube length or the number of branching points. Here we developed a high content analysis framework for detailed quantification of various aspects of network morphology including network complexity, symmetry and topology. By applying our approach to a high content screen of 1,280 characterised drugs, we found that drugs that result in a similar phenotype share the same mechanism of action or common downstream signalling pathways. our multiparametric analysis revealed that a group of glutamate receptor antagonists enhances branching and network connectivity. Using an integrative meta-analysis approach, we validated the link between these receptors and angiogenesis. We further found that the expression of these genes is associated with the prognosis of Alzheimer’s patients. In conclusion, our work shows that detailed image analysis of complex endothelial phenotypes can reveal new insights into biological mechanisms modulating the morphogenesis of endothelial networks and identify potential therapeutics for angiogenesis-related diseases.