雲端運算在醣基蛋白質體學量化分析之研究; The Study of Cloud Computing Used in Quantitative Analyzing in Glycoproteomics

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Title:	雲端運算在醣基蛋白質體學量化分析之研究;The Study of Cloud Computing Used in Quantitative Analyzing in Glycoproteomics
Authors:	蔡榕恒;TSAI,JUNG-HENG
Contributors:	通訊工程學系
Keywords:	雲端運算;MapReduce;蛋白質體學;醣基蛋白質體學;質譜分析;Cloud Computing;MapReduce;Proteomics;Glycoproteomics;Mass Spectrometry
Date:	2013-08-29
Issue Date:	2013-10-08 15:20:24 (UTC+8)
Publisher:	國立中央大學
Abstract:	近年來隨著生物科技蓬勃發展，蛋白質的研究一直是生物科技的重點之一，加上質譜技術日漸進步，分析蛋白質中各個胺基酸組成以及其各種諸如醣化、磷酸化修飾等變得更簡易。然而就算實驗時僅針對單一蛋白質，質譜儀所輸出的數據量仍舊龐大，以人工判讀方式往往需花上近半年之久。本論文將針對一種採用水解酵素消化蛋白質為胜?並搭配化學消去法產生斷醣訊號實驗，目的為找出O醣修飾胺基酸及O醣種類，對於實驗樣品經過質譜儀所輸出的資料做初步過濾篩檢，使資料量由數以千計減少為數十筆資料。此外，為了加速運算時間，本研究將資料篩選與檢測的程式利用雲端運算中的Hadoop架構所提供的MapReduce運算模式，將資料處理過程分散處理，降低運算時耗費的時間成本，讓醣蛋白質的鑑定得以從數個月大幅縮短為數天完成。 With the rapid development of biotechnology in recent years, the analysis of amino acid composition in protein such as glycosylation, phosphorylation, etc. has become easier due to mass spectrometry techniques. However, the amount of data output from mass spectrometer is large and substantial even if it in single protein experiments. In such situation, manual interpretation often costs nearly a half year. This paper will focus on finding O-glycopeptides and the O-glycoform modified on glycopeptide in protein-digesting hydrolysis enzyme with β-elimination method which produce peptidebackbone-18 signals in experimental sample data outputted through the mass spectrometer and doing preliminary filter, which can deduce the amount of data into dozens. In addition, to accelerate the computation time, we develop a cloud computing architecture that provides Hadoop MapReduce computing model. This kind of distributed computing reduce operational costs in time-consuming, so the time of finishing identification of glycoprotein would be shortened from several months into several days.
Appears in Collections:	[Graduate Institute of Communication Engineering] Electronic Thesis & Dissertation

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