以共調控人類基因的上游調控區預測轉錄調控模組之系統; A System for Prediction of Transcriptional Regulatory Modules in Human Upstream Control Regions of Coregulated Genes

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8714

Title:	以共調控人類基因的上游調控區預測轉錄調控模組之系統;A System for Prediction of Transcriptional Regulatory Modules in Human Upstream Control Regions of Coregulated Genes
Authors:	孫怡明;Yi-Ming Sun
Contributors:	資訊工程研究所
Keywords:	共調控;調控區;調控模組;regulatory module;coregulate;regulation
Date:	2003-06-25
Issue Date:	2009-09-22 11:33:27 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	基因晶片技術提供了大量顯現基因表現的方法，針對基因表現的狀況可以找出有相同表現結果的群組，基因調控機制在研究分子生物運作上是非常重要的議題，而找出基因調控點則是全面了解基因調控機制的重點之一。本研究之貢獻在於提出一個整合各種方法並能自動化進行調控點分析的系統。本研究發展了一個調控點預測系統，由使用者提供在調控機制上有相關性的基因群組，系統提供多種己被實際運用的預測程式(如Meme、gibbs、..)以及特殊序列(過度出現的重複序列、己知調控點)找尋各種可能的調控點，並提供相關的統計數值來協助過濾出比較重要的結果，接著利用找出的調控點資訊進行相關性分析來找出調控模組。經由整合在此系統的各個資料庫(TRANSFAC、HomoloDB、…)所提供的資訊，還可以提供使用者在進行分析時，能很方便地取得相關資訊來調整分析參數，來得到較佳的結果。系統同時提供個幾個不同的方法來呈現預測的結果，可以讓使用者更容易理解與決策。最後提供了實際分析的案例，來說明本系統的成效。 The microarray technology provides a method to reveal expression profiles of huge number genes. By using gene expression profiles, gene groups with the same expression pattern can be found. The mechanisms to regulate gene expression are an important subject in studying molecular biology. Finding transcriptional regulatory binding sites is one key point to totally understand gene expression regulation mechanisms. Therefore, an automatic system integrates various methods to analyze regulatory sites is the contribution of this study. In this study we develop a system to predict transcriptional regulatory binding sites. Using the gene group, which is correlated in regulatory mechanisms, is submitted by users. The system provides the followings to discover every possible regulatory site. 1. Various prediction programs (e.g. Meme, Gibbs, etc.) that are applied in many real cases. 2. Special sequences (e.g. over-represented repeat and known-site). It also provides useful statistical values to filter significant results. Then, by analyzing the association, we can use the information of candidate sites to find regulatory modules. The information in each databases integrated in this system can provide users to get some related information. This helps to adjust parameters efficiently in analyzing process for better results. The system also provides a lot of methods to represent prediction results. We will get more understanding and assistance to make decisions. At the end, we propose an analyzed real cases to describe the result of this system.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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