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Title: 利用數位訊號處理於基因預測之改善方式
Improved Digital Signal Processing Approach for Gene Prediction
Authors: Jia-Rong Chen
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: 滑動離散傅立葉轉換;改善的splicing 演算法;巴特理特視窗;放射狀基底網路;權種因子;蛋白質編碼區域
Sliding DFT;Splicing algorithm;Bartlett window;weighting factors;Radial Basis Function network;protein coding region
Date: 2005
Issue Date: 2011-06-22T08:47:02Z
Abstract: 摘 要 鑑別DNA序列的蛋白質編碼區域在基因計算辨認程序是最基礎的一個步驟。DNA序列之蛋白質編碼區域存在週期為三的特性是由於密碼子的組織。其此特性可以幫助預測基因位置,實際上也提供了數位訊號處理用在真核細胞的表現序列預測上。辨別蛋白質編碼區域常見的技術有離散傅立葉轉換與數位濾波器等方法。數位濾波器技術如splicing演算法與滑動離散傅立葉轉換可以作為辨別DNA序列之蛋白質編碼區域的工具。為了抑制DNA非編碼區域在2π/3的頻譜與改善正確編碼區域的可能性,此論文對於抑制非編碼區域提出了新方法。其主要是基於滑動離散傅立葉轉換與改善的splicing演算法,利用三種改善的方法:(1)巴特里特視窗;(2)加入權重因子;(3)利用放射狀基底網路平滑,希望能夠對於辨別DNA編碼區域有所改善,避免導致對於編碼區域的判斷錯誤。 關鍵詞:滑動離散傅立葉轉換、改善的splicing演算法、巴特里特視窗、權重因子、放射狀基底網路、DNA、蛋白質編碼區域。
Abstract Identifying protein coding regions in DNA sequences is a fundamental step in computational recognition of genes.It has been demonstrated that certain biological functions exhibit periodic behavior in DNA sequences, for example, the period-three behavior in protein-coding regions of DNA sequences due to codon structure. By allowing for discoveries in terms of these periodicities, it helps in predicting the gene locations, and in fact allows the prediction of specific exons within the genes of eucaryotic cells in the field of digital signal processing (DSP). The protein-coding regions are often identified with the help of techniques such as the discrete Fourier transform (DFT) and digital filter-based methods. Digital filtering techniques such as the Splicing algorithm and Sliding DFT (SDFT) can be used as tools to identify the protein coding region in a DNA sequence. To suppress the non-coding regions in the DNA spectrum at 2π/3 and improve the likelihood of correctly identifying coding regions, this paper exploits the new strategies that suppress the non-coding regions. The strategies include (1) use of the alternate windows such as the Bartlett window;(2) incorporation of the weighting factors in the algorithms;(3) use of the Radial Basis Function (RBF) network.Examples are given to illustrate the value of the proposed methods.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M93670009
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