Searching the Regulatory Protein Binding Site by Steepest Ascent Algorithm

[[abstract]]Gene transcription regulation impacts the final expression of gene. Generally gene expression is regulated via an interaction between regulatory proteins and specific DNA elements. If we find out the binding sites of regulatory factors, we could understand more of the control mechanism of gene transcription. For this reason, it is a very important issue to find out the regulatory factors of gene transcription. We propose a method to find out the regulatory protein binding sites from the comparisons of DNA sequences and scoring matrices. The steepest ascent algorithm is adopted to search the possible locations of binding sites. The predicted results of regulatory protein binding sites are shown with tables and charts. The proposed system in this paper will help biologists to analyze the regulatory protein binding sites more efficiently

Searching the Regulatory Protein Binding Site by Steepest Ascent Algorithm

[[abstract]]Gene transcription regulation impacts the final expression of gene. Generally gene expression is regulated via an interaction between regulatory proteins and specific DNA elements. If we find out the binding site of regulatory factors, we could un-derstand the mechanism of control of gene transcription more. For this reason, it is a very important issue to find out the regulatory factors of gene transcription. In this thesis, we try to find out the regulatory protein binding sites from the comparisons of DNA sequence and scoring matrices with suitable bio-conditions. The steepest ascent algorithm is adopted to search the possible locations of binding sites. The predicted results of regulatory protein binding sites are displayed with table and charts. The proposed system in this thesis will help the biologists to analyze the regu-latory protein binding sites efficiently, and to develop effective drugs for genetic dis-eases

Searching the Regulatory Protein Binding Site by Steepest Ascent Algorithm

[[abstract]]基因轉錄的調控影響了基因最終的表現結果，基因轉錄常是藉由一些調控蛋白與DNA上特定的區域交互作用來調節，因此尋找轉錄基因的調控因子在DNA上作用的位置，就可以幫助了解基因調控的機制。如何得到影響基因轉錄的調控因子結合區，便是一項意義重大的工作。 在本篇論文中，藉由基因序列和積分矩陣的比對，再考慮各種生物上的限制，我們應用陡升演算法尋找調控蛋白結合位置，找出最有可能的調控因子。同時，我們將基因序列的資訊及其結果之比較，用文字化和圖型化並存的方式顯現出來，以提供分子生物學家快速地找出一些基因的調控性蛋白結合位置，進而針對各個基因的特性，發展出更有效的藥物來解決不同基因所造成的遺傳性疾病

Searching the Regulatory Protein Binding Site by Steepest Ascent Algorithm

[[abstract]]"Gene transcription regulation impacts the final expression of gene. Generally gene expression is regulated via an interaction between regulatory proteins and specific DNA elements. If we find out the binding sites of regulatory factors, we could understand more of the control mechanism of gene transcription. For this reason, it is a very important issue to find out the regulatory factors of gene transcription. We propose a method to find out the regulatory protein binding sites from the comparisons of DNA sequences and scoring matrices. The steepest ascent algorithm is adopted to search the possible locations of binding sites. The predicted results of regulatory protein binding sites are shown with tables and charts. The proposed system in this paper will help biologists to analyze the regulatory protein binding sites more efficiently.

Searching the Regulatory Protein Binding Site by Steepest Ascent Algorithm

[[abstract]]Gene transcription regulation impacts the final expression of gene. Generally gene expression is regulated via an interaction between regulatory proteins and specific DNA elements. If we find out the binding sites of regulatory factors, we could understand more of the control mechanism of gene transcription. For this reason, it is a very important issue to find out the regulatory factors of gene transcription. We propose a method to find out the regulatory protein binding sites from the comparisons of DNA sequences and scoring matrices. The steepest ascent algorithm is adopted to search the possible locations of binding sites. The predicted results of regulatory protein binding sites are shown with tables and charts. The proposed system in this paper will help biologists to analyze the regulatory protein binding sites more efficiently