GDAP purpose

Gene-Disease Association Prediction (GDAP) is a tool designed to predict gene-disease associations using machine learning and node embeddings. By integrating data from sources like the STRING Database (for protein-protein interactions) and Open Targets (for disease-gene associations), GDAP constructs a bipartite graph where two distinct node types are represented: disease-gene and protein-protein. This graph captures relationships between genes and diseases, with edges representing known disease associations or protein-protein interactions. Node embeddings are generated using various algorithms to capture these relationships, which are then used for feature extraction to predict both known and novel gene-disease associations.