Project 3: Building & Learning biological knowledge
The goal of the project is to predict missing relationships between proteins, drugs, and diseases by learning from a biological knowledge GraphDB. We constructed the biological GraphDB consisting of nodes (32,373 proteins, 7815 drugs, 3721 diseases, etc.) and edges (55,618 drug-disease edges, 125,686 drug-protein edges, etc.) using knowledge from various open and private sources. Users can easily access and visualize the GraphDB via web browsers and navigate the DB using the Cypher query language. We are developing models to predict unknown links between the nodes (proteins, drugs, disease etc.) in the GraphDB. The models will be applied to finding new drug indications, new drug targets, and new disease biomarkers.
Status: In progress (September 2017)