基因表現資料分析軟體

Software for Gene Expression Data Analysis

戴維(JOSE DAVID DE LA BASTIDA CASTILLO)

指導教授 ： 陳朝欽

國立清華大學/電機資訊學院/資訊系統與應用研究所/碩士(2013年)

摘要

實驗研究DNA，RNA和蛋白質微陣列，通常包括數以千計的基因，可以生成大量的信息。處理完畢後，該信息將成為研究重點，以評估細胞或有機體的整體狀態的輸入數據。本工作的目的是提供用於快速和準確地處理任何微陣列數據集（與病人矩陣的相應的基因）的軟件工具，並在同一時間，提供經過這樣的基本步驟處理，以便獲得有用的結果。
我們的方法慨述如下：首先，我們將使用Fisher線性比單獨找到最好的K表代表性的特徵，我們利用分類和分群的技術以達精實結果並且以一維與二維樹狀圖形顯示結果。

關鍵字

聚類 ； 分類 ； 基因芯片 ； K-均值 ； 基因表達

並列摘要

ABSTRACT

Software for Gene Expression Data Analysis
By
José David de la Bastida Castillo

Experiments on DNA, RNA, and Protein microarrays, which normally include thousands of genes, can generate large volumes of information. Once processed, this information becomes the input data for researches focused to assess the overall state of a cell or an organism. The purpose of the present work is to provide software tools for processing any microarray dataset (given the corresponding gene versus patient matrix) fast and accurately; and, at the same time, to state the minimum steps required in order to obtain usable results after such processing.
The methodology is as follows: first, we will use the Fisher linear ratio to find the individually best k representative features, and then we will classify and cluster these findings, this to the aim of verifying the results. Finally, we will show a graphic interpretation of the outcome via dendrograms.

並列關鍵字

clustering ； classification ； microarray ； K-means ； gene expression

參考文獻

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