Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/52784
標題: 應用生物資訊學開發基因微陣列資料篩選及分析系統-以動物學習記憶實驗為例
Applying Bioninformatics to Develop a System That Can Filter and Analyze Microarray Data-Animal Learning and Memory Experiment as Case Study
作者: 蔡孟勳
沈炯祺
林立偉
關鍵字: 應用研究;Calcium channel;資訊科學軟體, 生物科學類;鈣離子通道;學習與記憶;微陣列;非監督式分群;類神經網路;基因調控網路;Learning and memory;Microarray;Unsupervisedclustering;Neural network;Gene regulatory network
摘要: 
腦科學的研究隨著時代漸趨熱門,這是由於人類的大腦仍存在許多未知的部份,研究者希望能藉由研究腦科學來預測並開發這些未知的區域,來提升人腦的運作效率;而微陣列是目前用來研究致病基因之工具中發展最為成熟的一項技術,通常被用來儲存及分析大量的數據資料,希望能發現疾病的致病路徑及標靶基因並藉此找到治療的方法。研究計畫預計分為兩年完成,第一年我們預計研發出一個能夠將微陣列資料進行分析及篩選的系統,並建立圖像化介面方便使用者使用。第二年預計將第一年所獲得的結果進行生物實驗,來驗證本計劃研發系統之正確性及在生物學上的意義。本研究計畫之主要目的為使用微陣列來針對具不同鈣離子通道表型的老鼠基因樣本進行實驗及分析,並採用不同的數學統計方法篩選可能的標靶基因,再以選出的基因用不同的分群方法檢視其是否具有分類性。由於微陣列的資料量都相當的龐大,且目前尚未有系統化的方法能夠對這些資料進行分析。因此,本研究計畫之系統除了分析資料外,更可減少生物實驗的時間及錯誤嘗試次數,藉以提高藥物開發的效率及病患的治癒率。而後這些篩選出的基因除了可被用在研究腦部疾病的治療方法外,也可用於腦部智力的開發工作,來提升個人的學習效果。

Brain science research becomes popular with times because there are still many unknownparts in the human brain. The researchers hope to improve the operational efficiency ofhuman brains by predicting and developing these unknown regions by researching brainscience. Presently microarray is the most mature technology of studying disease-causinggenes, it is used to store and analyze numerous data and hoping to discover treatment methodsby finding the path of disease pathogenesis and target genes. This project will be performedfor two years. In the first year, we will propose to develop a system that can filter and analyzemicroarray data and we will establish graphical interfaces to use for users. In the second year,we will use the results obtained in the first year to do biological experiments to verify theaccuracy of the developed system in this project and significance in biology. The mainpurpose of this project is to use microarray to do experiments and analyze the mice's genesamples with different calcium channel phenotypes. We also use different mathematicalstatistical methods to filter possible target genes, and then we use different clustering methodsto view classifications of these target genes. As the amount of microarray data is quite large,and there isn't a systematic method to analyze these data yet. Therefore the system of thisproject can not only analyze data, but also reduce the time of biological experiment and errorto enhance the efficiency of drug development and cured rates of patients. Then besides theseselected target genes are used to research the treatments for brain diseases, it can also be usedin intellectual development works to enhance their learning effects.
URI: http://hdl.handle.net/11455/52784
其他識別: NSC99-2221-E005-067
Appears in Collections:資訊管理學系

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