转录因子结合位点

转录因子结合位点作为一种转录调控元件，是基因组中具有调控功能的DNA序列片段，对其进行识别和预测将有助于解释基因表达调控的规律。

As transcriptional regulatory elements , TFBS are some kind of DNA sequence fragments , its recognition & prediction is the key of understanding the transcriptional regulatory mechanism and gene expression pattern .

转录因子结合位点的长度通常为5到20bp，相对于基因的转录起始位点（transcriptioninitialsite，TIS）有多种位置。

TFBS is usually 5 to 20 bp in length and situated variously relative to the transcription initial site ( TIS ) of a given gene .

预测酵母（Yeast）基因转录因子结合位点

Predicting Transcription Factor Binding Sites in a Yeast Genome

除了启动子以外，在几乎所有基因的上游区域中都还存在着激活基因所需的一段特定的DNA序列（转录因子结合位点）。

There are some specific DNA segments in the almost genes upstream region which is called transcription factor binding sites .

面对这个挑战的一个主要步骤就是识别调控元件，特别是识别DNA上的转录因子结合位点。

One of the most important steps is to find the regulators , especially the binding sites of the transcription factor .

基于二阶Z变换的转录因子结合位点识别方法研究

The Research of Identification of Transcription Factor Binding Site Based on Two-step Z Transform

转录因子结合位点是一种重要的转录调控元件，是基因组中具有调控功能的DNA序列片段。

The transcription factor binding sites is an important transcriptional regulatory elements . It is DNA segments which have certain regulatory function .

其中，转录因子结合位点是位于基因上游区域控制基因转录的一段DNA序列。

Transcription factor binding sites is a segment of DNA and located in the upper area of gene and control the transcription .

本文采用二阶Z变换对转录因子结合位点序列进行建模。

This paper models transcription factor binding sites ( TFBS ) using two-step Z transform .

DNA序列中的模体发现是生物信息学中最基本的问题，它涉及到基因的发现、转录因子结合位点的发现、启动子的发现等生物学问题。

Motif discovery in DNA sequences is a fundamental problem in bioinformatics , which relates to many biological problems such as gene finding , transcription factor binding site finding and promoter finding .

在真核生物中，多个转录因子结合位点组成顺式调控模块（CRM），对临近的基因的表达提供着更为复杂的调控功能。

In Eukaryote , several transcription factor binding sites constitute cis-regulatory module ( CRM ), providing more complex regulation for expression of neighboring genes .

通过重叠延伸PCR方法对其潜在的转录因子结合位点进行定点突变，检测各位点对FASN基因转录的调控作用。

The effect of transcriptional factor binding sites on promoter activity was detected via overlap extension PCR .

我们构建了包含FLOT2启动子和Wnt信号通路转录因子结合位点的荧光素酶报告基因载体。

We generated a luciferase reporter construct containing the Wnt signaling pathway transcription factor binding sites .

目的：预测人类BMP-2基因启动子位置和可能的转录因子结合位点。

Objective : To predict the promotor position and transcription factor binding sites of human BMP-2 gene .

HMM是一种强大的概率模型，它在识别转录因子结合位点中已有突出的成绩。

Hidden Markov Model is a strong probability model with math background , it had done very well in transcription factor binding sites finding .

根据测序获得的基因组序列，应用生物信息学方法对小鼠NPM的基因组结构及NPM基因5′启动子区可能的转录因子结合位点等进行了分析。

Based on the sequence , bioinformatics analysis on genomic structure of NPM and the transcription factor binding sites in the NPM 5 ′ flanking region were performed .

结论：肾上腺素α2A受体基因-1414&1025bp之间可能存在一转录因子结合位点，-1296位为C时，能与一特异性核蛋白结合，此蛋白质的相对分子量约为15kU。

CONCLUSION : There was a specific nuclear protein with molecular weight of 15 kU , which could bind with the binding site for transcriptor in the 390 bp fragment ( - 1414 & 1025 bp ) of adrenergic receptor alpha-2A gene with C at the site - 1296 bp .

结果：利用self-consistency和cross-validation两种方法对此算法进行检验，均获得了较高的预测成功率，结果表明5种转录因子结合位点的预测成功率均超过80%。

Results : By using of the self-consistency test and the 10-fold cross-validation test , prediction results show that the more than 80 % of correct prediction are obtained for all of five transcription factor binding sites .

进一步对RANTES启动子中不同转录因子结合位点进行突变分析，发现ISRE结合位点在CSFVNpro抑制RANTES中起重要作用。

Subsequently , mutation analysis was conducted on different transcription factor binding sites in RANTES promoter . It was shown that ISRE binding site played an important role in the inhibition of RANTES by CSFV Npro .

方法：构建转录因子结合位点位置权重矩阵，以转录因子结合位点每一位置的碱基保守性指数Mi为参量，利用位置权重打分函数算法（PWMSA）对酵母五种转录因子结合位点进行预测。

Methods : By constructing position weight matrix and calculating the site conservative index vectors Mi in transcription factor binding sites , a novel position weight matrix scoring algorithm ( PWMSA ) for predicting yeast transcription factor binding sites is presented .

转录因子结合位点和组合调控模式的研究

Prediction of Transcription Factor Binding Sites and Combinatorial Regulation of Eukaryotes

遗传算法在转录因子结合位点识别中的应用

Application of Genetic Algorithm in Recognition of Transcription Factor Binding Sites

本文介绍了一种利用转录因子结合位点应用计算机技术对人类肿瘤特异性启动子进行预测的方法。

A method of predicting human tumor peculiar promoter is introduced .

转录因子结合位点预测算法的研究与应用

Transcription Factor Binding Sites Prediction Algorithm Study and Application

基于遗传神经网络的转录因子结合位点识别方法研究

The Research for Recognition of Transcription Factor Binding Sites Based on Genetic-Neural Network

利用转录因子结合位点识别人类肿瘤特异性启动子研究

Predicting human tumor-specific promoter using transcription factor binding sites

将本方法应用于酵母的转录因子结合位点识别实验，取得了较好的结果。

This method has been applied to identifying yeast TFBS , and achieved better results .

本文使用一种基于图的方法识别转录因子结合位点。

In this article a graph-based approach is used to identify transcription factor binding sites .

目的：改进转录因子结合位点的理论预测方法。

Objective : To improve the predictive capacity of the algorithm for transcription factor binding sites .

利用序列保守模体和局部构象信息预测转录因子结合位点

Computational Prediction of Transcription Factor Binding Sites Based on Conserved Motif and Local Conformational Knowledge in Genomic Sequences