Finding Key Factors in Lung Cancer Drug Pathway over Biomedical Semantic Knowledge Network

摘要

The correlation and treatment of lung cancer have been the focus of biomedical research. To establish a semantic knowledge network of lung cancer, we adopted the following strategies: firstly, lung-cancer related data was effectively fused into the existing knowledge base. Then, the RDF triple was used to organize and describe the data. The semantic knowledge network was of great significance because it could be used to identify the genes, proteins, drugs, and other factors related to the disease. All these factors are very useful in the diagnosis, preconditioning, and treatment of lung cancer. In order to solve the big data problem, a distributed parallel framework of PageRank algorithm was used to identify the key data in lung cancer pathway. The experimental results indicate the efficacy of this novel method.