Applying Bioinformatics Methods to Detect the Relationship among Complex Diseases

With the development of high throughout SNP genotype sequencing technology, genetics epidemiology study has come into a new phase. Currently, using molecular network and protein structure information to research complex diseases and find related biology phenomena is a novel and powerful method. Here, we applied bioinformatics methods to analyze the topology properties, the signal peptide, the membrane spanning domain and the secondary structure of common susceptibility genes shared by different complex diseases, and therefore detected the relationship among these genes. In addition, based on the risk p-values of these shared genes for different diseases, an analysis of diseases relationship was performed. The results showed that the potential association among susceptibility genes of different diseases exists, which suggested it is possible to unravel the underlying molecular links between different diseases on a global scale. Our approach can provide an insight to molecular biology study and gene function exploration.