Research On Cancer Common Feature Analysis Method Based On Gene Expression Data

Cancer is one of the major public health problems in the world and has always threatened people’s lives and health.The occurrence and development of cancer is a very complicated process,so far people have not fully understood its pathogenesis.Understanding the pathogenesis of cancer and finding ways to treat and prevent can-cer has always been the goal pursued by humans.With the completion of the Human Genome Project and the development of High-throughput sequencing,a large number of gene expression data of cancer cells emerged to support cancer research and open up new perspectives for understanding pathogenesis of cancer.Abnormalities in sig-naling pathways and metabolic activities can lead to disturbances in cellular activity,which may cause cancer of living organisms.Therefore,study cancer common feature analysis method from differential signaling pathways and metabolic activities based on gene expression data is of great importance for understanding pathogenesis of cancer,detecting anti-cancer drug targets,and preventing cancers.In this dissertation,we conduct some research on cancer common feature analy-sis method based on gene expression data of cancer cells and normal cells.The main works include:(1)this study proposed a differential signaling pathway analysis method based on information divergence.Our method achieved the best performance based on sensitivity,priority,and false positives rate comparing with 5 classic methods.At the same time,we applied this method to a variety of gene expression data of cancer cells to predict significant differential signaling pathways and provide ideas for cancer re-search.(2)This study proposed a new method to reconstruct the differential metabolic network of cancer.This method successfully removed the tissue differences among different cancers and made it possible to better explore the common features of can-cer metabolism.(3)This study proposed a method to research the structural common features of cancer differential metabolic network,and successfully discovered the com-mon functional modules of cancer and so on.(4)This study proposed a method to study the common features of cancer metabolism based on the flow simulation,and predict potential anti-cancer drug targets.