↑ About PANDA System | 2. Select Training Set →
The mission of this study is as follows; Our purpose is to extract new disease-susceptible genes using H-InvDB. And our concept for extracting new candidate genes is that new candidates have similar character to reported disease related genes. Similar character means not only sequence homology or domain structure but also same metabolic pathway or expression pattern. H-InvDB has advantage of existence of these information on genes. So, based on this concept, we constructed Priority Analysis for Disease Association (PANDA) system On our methods, we used the 7 kinds of annotated information. Paralogous genes that result from a duplication anterior to the divergence of vertebrates have high degrees of similarity in their sequence and may share some redundancy in function. Genes associated with a disease may be identified through their functional similarities to known disease genes or their localization along the same physiological pathway as known disease genes. So, we compared among the genes based on InterPro, EC#, KEGG pathway, GO terms. Next, we transferred these information into score with some formula. We can get 7 kind of score in each gene. Finally, we tried to select the new disease-susceptible candidates with discriminant analysis.
↑ About PANDA System | 2. Select Training Set →