博碩士論文 962211012 完整後設資料紀錄

DC 欄位	值	語言
DC.contributor	系統生物與生物資訊研究所	zh_TW
DC.creator	王佩文	zh_TW
DC.creator	Pei-Wen Wang	en_US
dc.date.accessioned	2009-7-22T07:39:07Z
dc.date.available	2009-7-22T07:39:07Z
dc.date.issued	2009
dc.identifier.uri	http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=962211012
dc.contributor.department	系統生物與生物資訊研究所	zh_TW
DC.description	國立中央大學	zh_TW
DC.description	National Central University	en_US
dc.description.abstract	社會網絡已被應用在基因、蛋白質及代謝等各個領域來解釋其致病機轉。在這裡，我們利用醫院獲得醫療數據及由Online Mendelian Inheritance in Man ( OMIM)中取得基因與病徵等相關資料，藉由網路分析方法建立一個年齡動態疾病表現網絡（Age dynamic phenotypic disease network, ADPDN ），來分析不同年齡層下疾病網路的差異性。由結果顯示，當病人得到某個疾病時，伴隨得到第二種疾病的機率隨著年齡的增加而增加，而性別的不同也會造成差異。透過網路年齡的動態網路分析，證明疾病表現與疾病盛行率在基因層次上亦發現因為年齡及性別而有所不同，此方法結合醫療及基因資訊，建立疾病與基因的關聯性，期能對研究此相關領域者有所幫助。	zh_TW
dc.description.abstract	Social networks have been investigated on genetic, proteomic, and metabolic fields as a viable path toward elucidating the origins of specific diseases. Here we use epidemiology view to summarizing correlations obtained from hospital dataset in an age dynamic phenotypic disease network (ADPDN). We show the evidence that the progression of disease connect by the links of the network is different for patients according to age and genders. Our study show that human phenotypes and disease prevalence can be demonstrated and by using network analysis, facilitating the potential to enhance our understanding of the origin and evolution of human diseases.	en_US
DC.subject	疾病網路	zh_TW
DC.subject	疾病盛行率	zh_TW
DC.subject	動態網路	zh_TW
DC.subject	疾病組	zh_TW
DC.subject	表現型	zh_TW
DC.subject	dynamic network	en_US
DC.subject	disease network	en_US
DC.subject	disease prevalence	en_US
DC.subject	phenotype	en_US
DC.subject	diseaseome	en_US
DC.title	從年齡動態網路探討疾病表現與疾病盛行率	zh_TW
dc.language.iso	zh-TW	zh-TW
DC.title	An Age dynamic network for human phenotypes and disease prevalence	en_US
DC.type	博碩士論文	zh_TW
DC.type	thesis	en_US
DC.publisher	National Central University	en_US