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  • 學位論文

肝癌病患蛋白質體研究資料與臨床資料整合資訊管理系統

Development of a Laboratory Information Management System for Integrating of Diagnosis Proteomics and Patient Clinical Data in Hepatocellular carcinoma

指導教授 : 劉建財 邱泓文
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摘要


肝癌一直是台灣的重大疾病,而目前國內整合蛋白質體學及肝癌的研究,仍缺乏一個完善的肝癌蛋白質體整合研究資料管理系統。本研究主要利用動態網頁(Active server Pages,ASP)、web伺服器(Windows 2000 IIS)及資料庫(Microsoft Access),統合肝癌的診斷及蛋白質體研究資料,建構一個以web-based為基礎的肝癌蛋白質體研究資料管理系統。研究者可以透過瀏覽器同時取得肝癌診斷及蛋白質體的研究資訊。本系統主要提供下列功能包含:1建立實驗室資料管理系統,將實驗數據作有系統地存取和管理;2同時提供醫療診斷及蛋白質體資料檢視,不同構面的資料檢視協助發現肝癌早期診斷指標;3提供資料分享機制。本論文利用資訊工具,建立蛋白質體學資料管理系統:包括二維電泳影像比對和經質譜比對的蛋白質及連結至蛋白質資料庫的註解資訊。加上統合肝癌病患的基本資料如性別、血型、年齡,診斷資料中的癌症期別、病變部位,及肝功能的檢驗資料如GDP、GLP、ALB、TBIL等,整合成可呈現的數據,提供使用者更深入的資訊,有助於發現與肝癌的相關的蛋白指標(protein marker)。在瞭解該蛋白質功能後,就有可能找到致病原因,並發展出該疾病的檢測方法、藥物,治療方法。

並列摘要


Hepatocellular carcinoma (HCC or hepatoma) is the leading (20%) and the second (19%) cause for the mortality of male and female HCC population in Taiwan. There are increasing interests for researchers to identify novel biomarkers for HCC for the early detection and the developments of efficient therapy. An integrated-application system for the analysis of HCC data which features convenient storage and retrieving, and capable of analyzing complex information including clinical data, two-dimensional protein gel images, and specific protein was established in the study. This research take advantage of dynamic page, web Servers and database management system, developing a web-based laboratory information management system(LIMS) for integrating diagnosis proteomics and patient clinical data in HCC. The system also equipped with a powerful analytical application which can easily query for interesting protein spots and link these data to clinical information. Its web-based system further facilitates data sharing with international experts through internet easily and effectively. The three major functions that our system provide as follows: 1. LIMS (laboratory information management system): this system is equipped for the collection of proteomic data including two-dimensional protein gel images, information for specific protein spots of interesting, annotation of proteomic information, and the integration of patient’s clinical data. 2. Reference area: a web-based software tool was designed to quickly link to relevant data clinical data and protein databases. This is a research-driven approach to application. 3. Query management: a query form in which a user can specify the variety of parameters defined in the database to search the target data. Those query parameters include pathological section information (sample ID, source), Protein information (access number, protein name, molecular weight, pI), patient information (age, gender, cancer stage) clinical data (GOT, GPT, ALP, LDH, TBIL, DBIL), and others such as the parameters of an experiment protocol, date, operators. In conclusion, the system provide integrated data including patient’s pathological section data, patient data, clinical data, proteomic data and experimental protocols to facilitate researchers to investigate disease relationships with proteins. The LIMS also present the data combining proteomic experiment data and clinical data in a biological level, which is more meaningful to the researches.

參考文獻


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被引用紀錄


陳憶萱(2006)。智慧型醫療診斷模式建構於肝病診斷應用〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2006.00361

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