Registration of Protein Spots in 2D Gel Electrophoresis Images

碩士 === 淡江大學 === 資訊工程學系碩士班 === 95 === 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 p...

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Bibliographic Details
Main Authors: Shun-Chieh Yang, 楊順傑
Other Authors: Hui-Huang Hsu
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/59262899855964638252
Description
Summary:碩士 === 淡江大學 === 資訊工程學系碩士班 === 95 === 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.