还对化学信息学，生物信息学和系统生物学之间的新联系进行了探讨。
New links between chemoinformatics, bioinformatics, and systems biology are also explored.
一些生物信息学的计算工具。
利用生物信息学方法对检测结果进行分析。
The detected results were analyzed by bioinformatics method.
对突变片段行生物信息学及临床表现型分析。
The sequence alterations were analyzed by bioinformatics and phenotype.
RNA序列结构比对是生物信息学中的基本问题。
RNA sequence-structure alignment is a basic problem in bioinformatics.
基因网络相关的研究是生物信息学的重要研究领域。
Gene networks related research has now become one of the most important research areas in Bioinformatics.
RNA二级结构预测问题是生物信息学的一个研究重点。
One of the most important research areas in bioinformatics is RNA secondary structure prediction.
生物信息学是一门新兴的交叉学科，有它自身鲜明的特征。
Bioinformatics is a burgeoning cross discipline with its distinctive features.
所以对一个更好、更方便检索的生物信息学数据库的需求就更为迫切了。
So there's a growing need for a better, easily searchable bioinformatics database.
本文主要的研究内容是通用生物信息学数据库的设计和实现。
The content of this article is about the design and application of the general bioinformatics database.
表达序列标记和分子系统学分析，都隶属于生物信息学研究的范畴。
Both expressed sequence tags and phylogeny analysis are belonging to the field of bioinformatics.
生物信息学指的是：被设计成处理这些极大量信息的计算机软件技术。
Bioinformatics is the name given to the computer software technologies that are being devised to manage this information overload.
表面上他是一麻省理工生物系的研究员参于了生物信息学和新兴生物艺术学的研究。
He is, on paper, a research affiliate with their Department of Biology, and is involved in the study of bioinformatics and new biological art forms.
目前，如何在生物信息学教学中体现学科统一性仍然是一个未解决的课题。
At present, it is still an unresolved issue of how to embody subject unity at bioinformatics teaching.
集合覆盖贪心算法的推广被用来求解生物信息学中出现的冗余测试集问题。
The generalization of set cover greedy algorithm is used to solve the redundant test set problem arising in bioinformatics.
当代生物科学的进展—生物信息学—即是对以往的个别研究的归纳和演绎。
The current advances in biology (coming from bioinformatics in the post genomic era) are a direct result of the success of this reductionist approach.
生物信息学是一门新兴交叉学科，隐马模型是广泛用于该学科的数学模型。
Bioinformatics is a new cross-subject, and Hidden Markov models are widely used in it.
使用机器学习方法分析生物信息学中的复杂数据是目前重要的研究领域之一。
With the development of the bioinformatics, how to analyzes complex genomics data using machine learning approach has become an important research field.
作为基因功能预测的主要手段，序列相似性查询技术是生物信息学领域的研究热点。
As a main method for predicting the functionality of genes, the sequence similarity querying technique is becoming one of the research hotspots in bioinformatics.
生物信息学专业学习如何利用基金和方程序来整理和理解生物数据，包括基因数据。
Bioinformatics majors learn how to use computers and equations to sort and make sense of biological data, including genetic data.
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 structure prediction of proteins is the important problem of biology informatics. And the protein sequence is the base of the structure prediction of proteins.
这对数据模型选择上的冲击，反过来，是基于由生物学家提出的生物信息学数据的组织。
This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists.
目的：探讨砷化物与基因的相互作用，克隆砷相关基因，利用生物信息学技术分析克隆基因。
Objective: To explore the interaction of gene with arsenic compounds, arsenic related gene was cloned and its function was analyzed by bioinformatics.
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。
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.
这些实验方法已资助在高通量的基因组和表观基因技术，集成系统生物学和生物信息学的巨大进步。
These experimental approaches have been aided by tremendous advances in high-throughput genomic and epigenomic technologies, integrated systems biology and bioinformatics.
方法采用基因克隆、测序及生物信息学技术，分析HLA新等位基因与HLA已知基因序列的差异。
Methods Molecular cloning, sequencing and bioinformatics techniques were used to identify the difference between the new HLA allele and other known alleles.
方法采用基因克隆、测序及生物信息学技术，分析HLA新等位基因与HLA已知基因序列的差异。
Methods Molecular cloning, sequencing and bioinformatics techniques were used to identify the difference between the new HLA allele and other known alleles.
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