研究生: |
李季頴 Chi-Ying Lee |
---|---|
論文名稱: |
Automatic Nature-Size Translation with Object-Segmentation Data on Genotyping Polymorphic Bands of Microsatellite DNA 使用微衛星核酸遺傳多型條帶物件分割訊息自動解譯絕對長度 |
指導教授: |
陳朝欽
Chaur-Chin Chen |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 資訊系統與應用研究所 Institute of Information Systems and Applications |
論文出版年: | 2008 |
畢業學年度: | 96 |
語文別: | 英文 |
論文頁數: | 40 |
中文關鍵詞: | 自動影像處理 、自動自然長度轉譯 、物件分割 、物件分群 、標準長度 |
外文關鍵詞: | Automatic image data analysis (Aida), automatic nature-size translation (Anst), objects segmentation, objects grouping, size standards |
相關次數: | 點閱:2 下載:0 |
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Automatic image data analysis (Aida) with automatic nature-size translation (Anst) on object-segmentation data of genotyping polymorphic bands of microsatellite DNA requires routinely recovering size standards and especially translating nature size with merit in reproducibility and artifact-proof. The implemented Anst modules of Aida system [She2007] on object segmentation and data translation intends to provide efficient solutions in its semi-automatic format. This study with Anst module of Aida system automates parameter appropriation and nature size translation from serial data reports which apply both Peak method on band objects segmentation and Window method on lane objects grouping. Respectively, Peak method and Window method advantageously catches band objects from blear area and groups lanes in independent and homogenized format. Experimental results on ten data images with Anst module demonstrated 90~95% recovery ratio based on template sequence in automatic band recovery. While analyzing triplicate genotyping images of three running distances, the Anst module of Aida system along with in-house DNA size standards of MarkQoff (Marker-Quarter-Off) successfully translated nature size data of DNA fragments with mostly zero standard deviation and only one missing band. Yet, results of commercial BioNumerics software along with fifteen DNA size standards of SAGA on the same triplicate images translated sizes with up to 2.19 base pair of standard deviation along with the discrepancies of data floating points and two missing bands.
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