網絡是一種用來表示不同目標之間彼此關係的好方法，許多關於基因、蛋白質等各種與疾病相關的媒介與機轉，都可以透過網絡的方式來表示彼此之間的關連性。最近五年來，在公共衛生與醫療上，有許多應用網絡圖的方法來研究與呈現疾病與致命因子之間的影響。然而，我們利用衛生署健保局的醫療資訊與OMIM(Online Mendelian Inheritance in Man)上顯示有共同致病基因的疾病作配對，運用數學統計的方法以及網絡分析的技術建立一個疾病網路圖，藉由這些方法和資訊去探究基因與環境因子在現今流行病學上的影響程度。由最後的結果可以發現，在台灣社會裡，基因和其他致病因子如：年齡、性別、地區等，在疾病之間的發生率與誘導伴隨其他疾病的影響力，其他環境因子也是比較重要的關鍵角色。透過網路圖來分析疾病與致病因子的關係強弱，期許能對於研究疾病相關資訊和國人健康指標有助益。

A disease network has been developed in recent years. It is linked by genes and protein-protein interaction to show the relation between them and diseases. But there are still many unknown factors that have play an important role in disorders and epidemiology. We investigate the correlation between different popular diseases known by share genes on OMIM(Online Mendelian Inheritance in Man) and other risk factors such like sex and age. The chronic diseases such high blood pressure, osteoarthritis and cancers have a lot of other risk factors that affect people’s health, not just involved by genes. We not only check the diseases induced by genes from OMIM but also want to find whether the risk factors which have impacts on those diseases play a more important role in epidemiology. Maybe there are some diseases we have not found the correlation between each other. We attempt to construct a disease-disease network in a new relation and detect what doesn’t find between the diseases and human in epidemiology in Taiwan.

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