川崎症是一種罕見且病因不明的疾病，主要發生在幼齡兒童中，罹患川崎症的病患常伴隨者多種病徵，雖川崎症目前無法提前預防，但可以通過治療恢復，目前建議治療方式為使用免疫球蛋白以及阿斯匹靈再配合定期的追蹤檢查心臟超音波檢查。
現有川崎症資料庫Kawasaki Disease Database (KDD)僅提供了病患的臨床數據，無法提供生物學家找出與川崎症相關的基因，我們利用商業晶片中得到的DNA甲基化程度以及基因表現量，再利用統計手法分析兩群(川崎症治療前實驗組和發燒對照組)之間的有顯著差異可作為生物標記的基因，而這也構建出了我們的川崎症生物標記資料庫KDmakers，我們資料庫實做了四種不同的搜尋功能，讓生物學家根據不同情況來做使用，四種搜尋功能都具備了簡單明瞭的差異篩選、差異表格以及視覺化圖形，為了驗證本資料庫的正確性及實用性，我們從文獻中收集到關於川崎症的相關基因，其特性當川崎症患者與發燒對照組相比，DNA甲基化以及mRNA表現量都有顯著變化，而施予免疫球蛋白治療前後DNA甲基化以及mRNA表現量也會出現變化，故我們會利用搜尋模式二驗證那些基因看是否吻合論文敘述特性，接著我們會利用搜尋模式一蒐集出分別在DNA甲基化以及mRNA表現量特性相反的兩群基因列表，再利用生物特徵分析網站DAIVD進行特徵分析，將蒐集到的特徵進行統整。

Kawasaki disease is a rare disease with unknown etiology. It mainly occurs in young children. Patients suffering from Kawasaki disease are often accompanied by multiple symptoms. Although Kawasaki disease cannot be prevented in advance, it can be recovered through treatment. The current recommended treatment is use immunoglobulin and aspirin together with regular follow-up heart ultrasound examinations.
The existing Kawasaki Disease Database (KDD) only provides clinical data of patients and cannot provide biologists to find genes related to Kawasaki disease. We use the DNA methylation and gene expression from chips , and then using statistical methods to analyze the significant differences between the two groups (KD group before IVIG administration and the fever control group) that can be used as biomarker genes, and this has also constructed our database, a biomarker database for Kawasaki disease. The database has four different search functions for biologists to use according to different situations. The four search functions are equipped with simple and clear difference filtering, difference tables and visual graphics, in order to verify the correctness of the database. We have collected genes related to Kawasaki disease from the literature. Compared with the fever control group, Kawasaki disease patients have significant changes in DNA methylation and mRNA expression levels, and immunoglobulins are administered DNA methylation and mRNA expression levels will also change before and after treatment, so we will use search mode two to verify whether those genes match the characteristics described in the paper, and then we will use search mode one to collect the DNA methylation and mRNA expressions respectively The two groups of genes with opposite quantitative characteristics are listed, and then the biological characteristics analysis website DAIVD is used for characteristic analysis, and the collected characteristics are integrated.

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