Detecting disease genes based on semi-supervised learning and protein–protein interaction networks

摘要

ObjectivePredicting or prioritizing the human genes that cause disease, or “disease genes”, is one of the emerging tasks in biomedicine informatics. Research on network-based approach to this problem is carried out upon the key assumption of “the network-neighbour of a disease gene is likely to cause the same or a similar disease”, and mostly employs data regarding well-known disease genes, using supervised learning methods. This work aims to find an effective method to exploit the disease gene neighbourhood and the integration of several useful omics data sources, which potentially enhance disease gene predictions.