博碩士論文 110826003 詳細資訊




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姓名 邱潔薇(Jie-Wei Chiu)  查詢紙本館藏   畢業系所 系統生物與生物資訊研究所
論文名稱 DeNox:代謝體學與蛋白質體學定量數據的可視化工具
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摘要(中) 液相層析串聯質譜 (LC-MS/MS) 技術已成為代謝體學與蛋白質體學的主要平台。獲得的 LC-MS/MS 數據由可用的軟體工具處理,用於分子鑑定和定量。數據可視化是一種直接的品質檢測解決方式,因為用戶可以直接檢查 LC-MS/MS 數據中的原始信號和雜訊。然而,人工檢查是一項耗時的工作,尤其是對於包含數千個 LC-MS/MS 文件的數據集。必須有一個軟體工具可以自動從 LC-MS/MS 代謝體學和蛋白質體學數據中提取特徵峰,導出圖形以供用戶輕鬆檢查信號。因此,我們開發了一個名為 DeNox 的可視化工具,它可以有效地從 LC-MS 數據中提取信號並以三幅圖呈現信號,包括 (1) 洗脫熱圖 (滯留時間為 橫軸,質荷比為縱軸),(2) 質譜信息 (質荷比為橫軸,信號強度為縱軸),以及 (3) 萃取離子層析圖 (滯留時間為橫軸,信號強度為縱軸)。我們的工具亦提供八個測量值供用戶檢查定量的代謝物和鑑定的肽的品質,提高定量/鑑定結果的準確性和可靠性。此軟體已公開上傳於GitHub以供下載:https://github.com/ICMOL/DeNox。
摘要(英) Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become a predominant platform for metabolomics and proteomics.The acquired LC-MS/MS data are processed by available software tools for molecular identification and quantitation. Data visualization is a straightforward solution for quality inspection because users can directly exam raw signals and noises in LC-MS/MS data. Nevertheless, manual inspection is a time-consuming work, especially for a dataset with thousands of LC-MS/MS files. It is essential to have a software tool which can automatically extract feature peaks from LC-MS/MS metabolomics and proteomics data, exporting figures for users to easily exam the signals. We thus developed a visualization tool, called DeNox, which can efficiently extract signals from LC-MS data and present the signals in three figures, including (1) an elution profile (the retention time as the x-axis and m/z as the y-axis), (2) a spectrum information (the m/z as the x-axis and intensity as the y-axis), and (3) an extracted ion chromatogram (the retention time as the x-axis and intensity as the y-axis). Our tool also provides eight measures for users to inspect the quality of quantified metabolites and identified peptides, improving the accuracy and reliability of quantitation/identification results. The software tool is now available at: https://github.com/ICMOL/DeNox.
關鍵字(中) ★ LC-MS/MS
★ 代謝體學
★ 蛋白質體學
★ 可視化數據
★ 軟體工具
關鍵字(英)
論文目次 中文摘要 i
Abstract ii
致謝 iv
目錄 v
圖目錄 vii
表目錄 viii
一、 緒論 1
1-1 質譜分析技術 1
1-2 解析質譜圖 3
1-3 解析層析圖 5
1-4 研究動機 7
二、 材料方法 8
2-1 代謝體學和蛋白質體學數據來源與特徵資料 8
2-2 DeNox工作流程 9
2-3 峰值品質評估指標 11
三、 結果與討論 14
3-1 DeNox介面展示 14
3-1-1 參數設定頁面 14
3-1-2 視覺化圖表頁面 16
3-2 軟體性能評估 19
3-2-1 代謝體資料分析 19
3-2-2 蛋白質體資料分析 21
3-3 層析峰品質評估 22
3-3-1 代謝體資料 - 層析峰案例評估 22
3-3-2 蛋白質體資料 - 層析峰案例評估 25
3-3-3 代謝體學實驗性指標評估情形 28
3-3-4 蛋白質體學實驗性指標評估情形 30
3-4 質譜信號可視化 31
3-4-1 總離子電流 31
3-4-2 噴霧不穩問題 33
3-4-3 檢視背景信號 35
3-4-4 同位素 36
3-4-5 共洗脫 38
四、 結論 40
參考文獻 41
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指導教授 張彙音(Hui-Yin Chang) 審核日期 2023-7-14
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