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    題名: 二維凝膠電泳影像中蛋白質點的比對
    其他題名: Registration of protein spots in 2D gel electrophoresis images
    作者: 楊順傑;Yang, Shun-chieh
    貢獻者: 淡江大學資訊工程學系碩士班
    許輝煌;Hsu, Hui-huang
    關鍵詞: 比對;二維凝膠;蛋白質;電泳影像;薄板曲線;Registration;2D Gel Electrophoresis;Protein;Matching;Thin-Plate Spline
    日期: 2007
    上傳時間: 2010-01-11 06:01:00 (UTC+8)
    摘要: 二維凝膠電泳一直是研究蛋白質上非常重要的一項工具,但是我們必須對凝膠影像作一些處理,才可以從中得到所要的資訊。這些處理過程像是蛋白質點的偵測和比對,若是以人工的方式來做這些分析,需費大量時間外,結果也常常不盡理想。所以我們希望能夠設計一套系統,來幫助相關的研究員能夠方便且迅速的分析結果。例如今天我們有兩張未感染病菌及受感染病菌的二維凝膠電泳影像,因為其中的蛋白質會因為有無感染病菌而有不同的變化,我們先利用之前所偵測出來的結果,來判斷兩張二維凝膠電泳影像上,是不是有哪些蛋白質點產生變化:變大、變小、變濃、變淡或是消失等等。這些蛋白質點就是我們感興趣的,也是作此研究的目的所在,因為這表示了這些蛋白質點在感染了特種病菌之後,會產生反應和變化。因此,我們就根據蛋白質體研究者的需求,設計了這樣的一套系統。系統中,我們主要將先前在二維凝膠電泳影像上所偵測出來的蛋白質點,作後續的比對功能,在這邊我們使用了數學上的方法,先找出幾組對應點當作我們的基準點,再經由這些基準點找出兩張圖上點之間的數學轉換方程式,使其上每個點都能夠滿足這樣的一個方程式;另外我們也根據圖上點的資訊,作些微的調整,以達到所需的比對功能。最後,我們再依據使用者的要求,呈現比對的結果,使得使用者能夠很快的得到他們所要的結果,以便做更進一步的分析。最後,我們將實作後的比對結果顯示出來,說明此系統的比對結果是非常良好的。
    In proteomics, 2D gel electrophoresis plays a very important role. We need some processes on these 2D gel electrophoresis images to get information we want. These processes include detection and registration of protein spots. Traditionally, researchers can pick protein spots in the gel images manually. As a result, they spent much time but still made mistakes. For this reason, we proposed a system to assist researchers in dealing with this problem and analyzing protein characteristics. For instance, we got two 2D gel images. One is protein with germs infective, the other is protein with germs anti-infective. In two images, protein spots are different from each other. We take results of detection of protein spots to determine if protein spots change in two images. These changes like getting bigger or smaller, darker or lighter, even disappearing. And, these protein spots are what we are interested. Therefore, we design a system in accordance with demands of researchers. In this system, we mainly take results of detection of protein spots in 2D gel images and develop follow-up capability of matching protein spots. We use methods on mathematics, that is, to select several pairs of spots in two images as landmarks, and then we can find an equation that could transform the source image into the target image. Thus, all spots in images will satisfy this equation and our aim to match these protein spots will be achieved. We show our results of matching depending on demands of users to let them get results efficiently.
    顯示於類別:[資訊工程學系暨研究所] 學位論文

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