剪接位点

基于结合HM-SVM方法的HMM剪接位点识别研究

Splice site identification based on Hidden Markov model combining with hm-svm

基于改进的Winnow算法的剪接位点识别

Splice Site Identification Based on Improved Winnow Algorithm

基于贝叶斯网络的DNA序列剪接位点预测

Predicting splice junction site in DNA sequences with Bayesian network

用神经网络法预测mRNA的剪接位点

Predicting the splicing sites of mRNA by neural network

隐Markov模型在剪接位点识别中的应用

Application of hidden Markov model in the recognition of splicing sites

采用基于贝叶斯网络的建模方法，预测真核生物DNA序列中的剪接位点。

Two new models for predicting the splice junction in eukaryotic DNA sequences were developed by exploiting Bayesian network , one for donor site and the other for acceptor site .

为了对剪接位点取得更加精确的预测结果，采用HMM方法设计并构建了剪接位点识别系统。

The HMM algorithm is adopted for better prediction performance of splice sites in designing and constructing the splice site identification system .

通过信号检索的途径对剪接位点进行了分析，并将基于Z曲线理论开发的DNA序列新分段算法应用到这一问题中。

As to the splice sites , we analyze them through a signal search way and apply a new segmentation algorithm for DNA sequences which is based on the Z curve method .

大珠母贝pmAMY基因的2个内含子都起始于GT，终止于AG，符合内含子共同剪接位点序列。

Both of the two introns sequences began from GT and ended as AG , which was consistent with common sequences of intron splice sites . 4 .

SR蛋白是具有帮助识别正确剪接位点并促进剪接体的成熟的一类重要剪接因子，为组成性剪接所必需，在选择性剪接中更起着不可替代的作用。

SR protein is a kind of splicing factors that help recognition splicing site correctly and promote mature of splicesome , they are essential to constitutive splicing and have pivotal contribution to alternative splicing .

它们可以结合特定的RNA，参与识别5′及3′剪接位点，与snRNP及其他剪接因子共同完成RNA的组成性和选择性剪接。

They can bind specific RNA , recognize 5 ′ and 3 ′ splice site , help to complete RNA constitutive and alternative splicing with snRNP and other splicing factors .

结论该剪接位点突变可影响基因转录和翻译产物，是ATP2C1基因新的特异性突变。

Conclusion The splicing mutation can affect the result of transcription and translation , and it is a specific novel mutation of ATP2C1 gene .

依据剪接位点附近存在的序列保守性，将联合核函数学习融入最大边缘分类器，结合HM-SVM工作集最优化算法，构建并生成了健壮分类器。

According to the conservation feature in the vicinity of splice sites , the joint kernel learning is syncretized into the maximum margin classifier , and combining the HM - SVM training set optimization algorithm , a robust classifier is designed and generated here .

使用估计的反应自由能预测组成性和可变剪接位点

Employing estimative reaction free energy to recognize constitutive and alternative splice sites

基于特征挖掘与融合的剪接位点识别

Identification of splice sites based on feature mining and integration

基于支持向量机的人类5'非翻译区剪接位点识别

Identification of 5'UTRs splice sites in human gene based on support vector machine

真核基因剪接位点二级结构特征

Secondary structural characteristic of eukaryotic gene splicing sites

模式生物基因组中可变剪接位点的预测及序列特征分析

Prediction of Alternative Splice Site and Analysis of Sequence Characteristic in Model Organism Genome

内含子与外显子的剪接位点符合常规GT/AG剪接位点特征。

The splice sites between exons and introns was following GT / AG splicing rule .

内含子二级结构与剪接位点

Secondary structures of introns and splicing sites

精确预测剪接位点是真核基因系统研究的第一步。

Accurate prediction for splice sites is the primary step in the system research for eukaryotic genes .

隐蔽剪接位点：与剪接位点序列相似，但一般不进行剪接的位置。

Cryptic splice site & A DNA sequence similar to the consensus splice site but not normally used .

利用多样性增量位置得分函数预测人类5'非翻译区剪接位点

Prediction of splice sites in human 5'UTRs by use of position score funtion based on increment of diversity

真核基因非翻译区剪接位点识别算法的研究。

The research on method for splice sites identification in eukaryotic gene untranslated coding regions ( UTR ) .

当把理论应用到剪接位点及其侧翼竞争者的预测问题时，获得了较高的预测精度。

When the theory is employed to predict splice sites and their flanking competitors , higher prediction accuracy is obtained .

主要的研究工作如下：一、真核基因编码区剪接位点识别算法的研究。

The central work as follows : 1 . The research on method for splice sites identification in eukaryotic gene coding regions .

统计分析了盒式外显子和组成性外显子的序列长度、长度被3整除序列的比例、两侧剪接位点保守性等序列特征。

The skipped exons and constitutive exons are analyzed for its length , the divisibility by 3 and the splice site conservation .

使用该方法对真实剪接位点和虚假剪接位点进行识别，识别率均可达90%以上。

Applying the method to recognize both the true and false splicing sites , the recognition rates are greater than 90 % .

对其剪接位点的分析，发现两段染色体序列存在的重叠区可能在这种剪接中起着重要作用。

Over lapping regions between splicing sites on both chromosomes were observed , which would play an important role in the interchromosomal trans-splicing .

最大信息原理、能量及选择约束在基因剪接位点预测分析中应用的研究

Studies on the Application of Maximum Information Principle , Energy and Selection Constraints to the Prediction and Analysis of Splice Sites in Genes