| Summary: | 碩士 === 長庚大學 === 資訊管理學系 === 99 === After finishing gene sequencing, most researchers focused on functional genomics and proteomics. Information technologies can not only be applied on mass database analysis and keep any human resources and time from wasting, but also present an analysis by using graphical illustration. Phosphorylate is one of the most critical factors in post-translational modifications for protein. Many researchers used data mining in analyzing phosphorylation site and related studies. The hierarchical clusters analysis method in data mining has been widely used in biomedicine, but most of them accept only numeric data. So far, the graphical illustrating programs which process the phosphorylation sequence databases are still using the sequence logo to mark out the frequency of the amino acid residues from a single sequence database, but not analyze the differences and the locations between multiple databases. Java Treeview offers the hierarchical clusters analysis to deal with the tree map and mosaic pattern matrix map, and be able to visualize the structures and the differences and trends between clusters but visualize only numeric data, which is inapplicable for the protein phosphorylation sequence analysis. Therefore, our research developed one software that is now be able to visualize the hierarchical clustering analysis on the database of protein phosphorylation sequence by taking the reference on Java Treeview. We also added the sequence logo analysis method which offers more comprehensive graphical illustrations, and enable any researchers to cross match several databases of protein phosphorylation sequence at a time.
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