二级结构预测

质心法：受类别驱动的RNA二级结构预测方法

Centroid : RNA secondary structure prediction approach based on class information

RNA二级结构预测算法的设计与实现

Design and Implementation of an Algorithm for the RNA Secondary Structure Prediction

DNA单链二级结构预测与单链构象多态性分析的一致性研究

The Comparison of Predicted Second Structure of DNA Single Strand with Single Strand Conformation Polymorphism Analysis Results

计算最大堆迭的RNA二级结构预测算法

The Predicting Algorithm of RNA Secondary Structure for Computing Maximum Stacking

基于堆积能量和协变信息的RNA二级结构预测算法

Prediction of RNA secondary structure based on stacking energy and covariance

基于螺旋区随机堆积的RNA二级结构预测

Prediction of RNA secondary structure based on random stacking of helical regions

蛋白质二级结构预测结果表明，3个ω-3脂肪酸脱氢酶蛋白主要由α螺旋和p折叠组成。

Protein second-structure indicated that safflower ω - 3 fatty acid desaturase were composed by α - helix and β - sheet .

基于SqlServer的蛋白质二级结构预测样本集数据库的构建

Constitution of database on data sets for prediction of protein secondary structures based on SQL server

基于局部茎搜索的RNA二级结构预测算法

A Local-stem-search Algorithm to Predict The RNA Secondary Structure

RNA二级结构预测算法分析与比较

Analysis and Comparison on RNA Secondary Structure Prediction Algorithm

面向FPGA的RNA二级结构预测并行算法研究

FPGA-Oriented Fine-Grained Algorithm for RNA Secondary Structure Prediction

RNA二级结构预测的神经网络方法

Neural network approach to predict RNA secondary structures

RNA二级结构预测方法

The methods of RNA secondary structure prediction

利用BP神经网络，建立了蛋白质二级结构预测的评测模型。

Using the BP nerve network , this paper established the evaluation model of protein secondary structure prediction .

蛋白质二级结构预测中的HMM及I/OHMM方法研究

Research of HMM and I / O HMM used in protein secondary structure prediction

为了提高蛋白质二级结构预测精度，本文尝试采用一种基于串联BP网络集成的二级结构预测模型。

To improve the prediction results of protein secondary structure , we developed a neural network ensemble model based on dual-layer feed forward BP network .

RNA二级结构预测方法可以分为基于热力学的预测方法和基于系统发生学的预测方法两大类。

The methods for RNA secondary structure prediction can be divided into two categories which are the methods based on thermodynamics and phylogenetics .

RNA序列的研究方法主要有两个大的方向，分别是基于多序列比较分析方法的RNA二级结构预测方法和基于单序列的RNA二级结构预测方法。

They are the RNA secondary structure prediction methods based on multiple comparative sequence analysis and RNA secondary structure prediction methods based on a single sequence .

方法：用RNA二级结构预测程序预测bcl2mRNA的二级结构；

Method : The computer messenger RNA secondary structure prediction software was utilized to predict the optimal and sub optimal secondary structures of human bcl 2 mRNA .

RNA二级结构预测是近年来RNA研究的热点问题，研究者提出了多种预测算法，并取得了丰富的成果。

The prediction of RNA secondary structure is a hotspot in RNA research . Many secondary structure prediction methods have been presented and rich results have been achieved .

应用标准隐Markov模型进行蛋白质二级结构预测时，必须根据同源家族蛋白库进行学习训练，从已有的知识出发进行二级结构预测。

When applying the standard hidden Markov model to predict the protein secondary structure , we must set out from the knowledge according to homological protein secondary structure database .

提出了基于螺旋区随机堆积的RNA二级结构预测算法，包括三个步骤：1.根据螺旋区定义，找出所有可能螺旋区；

We present a computer method to predict RNA secondary structures which is based on helical regions random stacking and consists of three steps : 1.List all possible helical regions .

实验结果显示，用富含“生物进化信息”的Profile编码方式可以得到较高的预测结果，同时也表明，充分利用生物本身所具有的生物信息对提高蛋白质二级结构预测精度是非常重要的。

Results indicated that Profile encoding that preserves the redundant evolutionary information got higher prediction performance , and that how to use biologic evolutionary information effectively is very important to improve accuracy of protein secondary structure prediction .

分析了碱基最大配对、极小化自由能、螺旋区组合和基于多序列比较的RNA二级结构预测等典型算法的优劣；

The advantages and weakness of typical algorithms including maximum base pair , minimum free energy , combination of helical regions , prediction of RNA secondary structure based on multiple sequences alignment , and etc.

在线用蛋白质二级结构预测软件分析MAGE-4抗原表位，PCR获取MAGE-4抗原特征表位基因。

Analyze MAGE-4 antigen epitope by online predict software of protein secondary structure and amplify the epitope gene by PCR .

肿瘤抗原MAGE-12的表位及二级结构预测

Predication of secondary structures and epitopes of tumor antigen MAGE-12

通过现有的序列同源性比较、二级结构预测、三维结构预测和模拟方法，得到了拟南芥中PAP特异磷酸酶的三维结构。

The three dimensional structure of Arabidopsis thaliana PAP-specific phosphatase was predicted by use of various existing methods on sequence comparison , secondary structure prediction , three dimensional structure prediction and simulation .

基于miRNA相似性序列和二级结构预测，从克隆测序的156639序列中发现63个miRNA属于42个高度保守的miRNA家族，与已知miRNA的完全匹配。

Based on sequence similarity and hairpin structure prediction , we found that 156,639 reads representing 63 sequences from 42 highly conserved miRNA families , have perfect matches to known miRNAs .

基于GEP-BP网络集成的蛋白质二级结构预测方法研究

Study of protein secondary structure prediction methods based on GEP-BP network ensemble

GP-MaxEnt模型的蛋白质二级结构预测

Protein secondary structure prediction based on GP-MaxEnt model