RNA secondary structure prediction is one of the most important fields in computational molecular biology.
RNA二级结构预测是计算分子生物学中的一个重要领域。
Protein structure prediction has proven to be one of the central problems in the field of computational biology.
蛋白质结构预测问题是计算生物学领域的核心问题之一。
The experimental results from the protein structure prediction demonstrate that the model is effective and promising.
实验研究结果表明本文所提出的模型是有效的并具有良好的发展前景。
Multiple sequence alignment is one of the essential tools of studying bioinformatics and it plays an important role in the evolution analysis and protein structure prediction.
多序列比对是一种重要的生物信息学工具，在生物的进化分析以及蛋白质的结构预测方面有著重要的应用。
Similarity searches are a powerful method for solving important biological problems such as database scanning, evolutionary studies, gene prediction, and protein structure prediction.
相似性搜索是解决重要的生物学问题，例如数据库扫描、进化研究、基因预测和蛋白质结构预测的一种强大的方法。
This paper focuses on the prosodic structure prediction model.
本文重点研究了韵律结构预测模型。
Designing a scoring function plays a key role in protein structure prediction.
评分函数设计是预测蛋白质结构的关键之一。
One of the most important research areas in bioinformatics is RNA secondary structure prediction.
RNA二级结构预测问题是生物信息学的一个研究重点。
Proteomics strategy tools usually focus on similarity searches, structure prediction, and protein modeling.
蛋白质组学战略工具通常集中于相似性搜索，结构预测，蛋白质模型建立。
Protein structure prediction problem is to predict the dimensional folding configurations from its amino acid sequence.
蛋白质构形预测问题就是根据组成蛋白质的氨基酸序列来预测其空间折叠结构。
We discuss some developments in this area, including off-lattice structure prediction using the great deluge algorithm.
我们讨论了这个领域的一些进展，包括使用大洪水算法进行的非晶格结构预测。
Protein secondary structure prediction is a fundamental and important component in the study of protein structure and functions.
蛋白质二级结构是研究蛋白质结构和功能的基础和重要组成部分。
Protein secondary structure prediction becomes the most important step of predicting the space conformation from protein molecule.
蛋白质二级结构预测是蛋白质结构预测的重要组成部分，是蛋白质结构预测最关键的步骤。
Create flowcharts, top-down diagrams, information tracking diagrams, process planning diagrams, and structure prediction diagrams.
用于创建流程图、顺序图、信息跟踪图、流程规划图和结构预测图。
Numerical tests illustrate that the memory Tabu search algorithm is feasible and effective to protein structure prediction problems.
数值实验表明该算法对于蛋白质结构预测是可行有效的。
In the paper, an improved TS algorithm is proposed for protein Three-Dimensional (3d) folding structure prediction in AB off-lattice model.
基于AB非格模型，该文将一种改进的禁忌搜索算法应用于蛋白质三维折叠结构预测。
The methods for RNA secondary structure prediction can be divided into two categories which are the methods based on thermodynamics and phylogenetics.
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。
Using a new neighborhood structure and partly randomized off-trap strategy, a novel local search algorithm for protein structure prediction is proposed.
构造了新的邻域结构，采用了部分随机跳坑策略，对此问题提出了新的局部搜索算法。
Research on conformational space of protein structure in which proteins take clear regulation plays a key role in protein structure prediction and simulation.
蛋白质结构构象呈现明显的规律，研究其在特定构象空间的分布对蛋白质结构预测和模拟具有重要意义。
Create flowcharts, top-down diagrams, information tracking diagrams, process planning diagrams, and structure prediction diagrams. Contains connectors and links.
创建流程图、顺序图、信息跟踪图、流程规划图和结构预测图。包含连接线和链接。
The biological sequence analysis research content mainly includes the sequence alignment, the protein structure prediction, and the genome sequence analysis etc.
生物序列分析的主要研究内容包括序列比对、蛋白质结构预测、基因组序列分析等。
Use for flowcharts, top-down diagrams, information tracking diagrams, process planning diagrams, and structure prediction diagrams. Contains connectors and links.
用于创建流程图、顺序图、信息跟踪图、流程规划图和结构预测图。包含连接线和链接。
The structure prediction of proteins is the important problem of biology informatics. And the protein sequence is the base of the structure prediction of proteins.
蛋白质结构预测是生物信息学中的重要课题，而蛋白质序列是蛋白质结构预测的基础。
The protein structure prediction is a main direction in bioinformatics, and the prediction of protein contact maps is an important content in protein structure prediction.
蛋白质结构预测是生物信息学的一个主要研究方向，而蛋白质关联图预测是其中的一个重要内容。
Aiming at solving the complicated non-linear pattern classification problem of protein secondary structure prediction, a new method based on radial basis function is proposed.
文章针对蛋白质二级结构预测这一复杂非线性模式分类问题，提出了基于径向基函数的预测方法。
The experiments show that the rule-learning approach can achieve a better accuracy rate of 90% than the others. Thus it is justified as an effective way to prosodic structure prediction.
实践表明，规则学习算法用于韵律结构预测达到了90％以上的正确率，优于目前其他方法的结果，是一种行之有效的办法。
It is generally accepted that amino acid sequences determine the spatial structures of proteins. Protein structure prediction methods are explicitly or implicitly based on this assumption.
氨基酸序列决定蛋白质高级结构是普遍接受的假设，也是蛋白质结构预测的理论基础。
Protein structure prediction has matured over the past few years to the point that even fully automated methods can provide reasonably accurate three-dimensional models of protein structures.
蛋白质结构预测在过去的几年里已经成熟到甚至完全自动的方法就能够提供相当准确的蛋白质结构的三维模型的程度。
Structure prediction and protein design are closely related.
蛋白质设计和蛋白质结构预测是紧密相关的。
This is a web page of Classification and Secondary Structure Prediction of Membrane Proteins.
这是膜蛋白分类和二级结构预测在线工具的网页。
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