生物序列分析

隐马尔可夫模型（HMM）是一个能够通过可观察的数据很好地捕捉真实空间统计性质的随机模型，该模型用于生物序列分析是生物信息学（Bioinformatics）研究的新领域。

Hidden Markov Models ( HMM ) is a stochastic model that accurately captures the statistical properties of observed data . The utilization of HMM is a new field of Bioinformatics in the research of biological sequence analysis .

生物序列分析则是生物信息学领域重要的基础性研究工作。

Biological sequence analysis has become a fundamental task of bioinformatics .

迭代函数系统模型在生物序列分析中的应用

Application of iterated function systems model to biological sequence analysis

含先验信息的学习机在生物序列分析中的应用

Application of prior-knowledge-bearing learning machine in biological sequence analysis

基于支持向量机的生物序列分析

Analysis of Biology Sequences Based on Support Vector Machine

贝叶斯神经网络在生物序列分析中的应用

Application of Bayesian Neural Networks to Biological Sequence Analysis

核学习方法及其在生物序列分析中的应用

Kernel Methods for Biological Sequence Analysis

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。

The biological sequence analysis research content mainly includes the sequence alignment , the protein structure prediction , and the genome sequence analysis etc.

传统的蛋白质相似性分析方法主要是一些以序列比对为主的一维生物序列分析方法，这一类算法往往在计算的时间和空间复杂度上具有明显的优势，但同时也有很大的局限性。

Traditional methods that be used to analysis those one-dimensional amino acid sequences usually have obvious advantage in the time and space complexity . But they also have some limitations .

近年来，随着生物学实验数据的爆炸式增长，机器学习方法在生物序列分析和重要信息的提取中发挥着越来越重要的作用。

Recently , due to the explosive growth of the available biological data , machine learning methods have become increasingly important for analyzing biological sequence and extracting important information from it .

目前已成为机器学习领域的研究热点，但其应用方面的研究刚刚开始，在文本分类，图像分类、生物序列分析等方面得到成功应用。

SVMs have drawn much attention in the fields of machine learning due to their good performance and have been successfully applied into note classification , image classification and DNA sorting etc.

生物序列分析是生物信息学的主要研究领域，其任务是从浩瀚的生物序列数据中发掘知识和揭示生命的奥秘。

The biological sequence analysis is the main research area in bioinformatics , and its primary mission is to mining knowledge from the massive biological sequences , and to explore the mystery of the life .

本文致力于生物序列分析的研究领域，提出具有一定特色的比较分析模型。通常，序列的比较分析主要被分成两类模型：比对模型和非比对模型。

In this dissertation , we focus on the field of the biological sequence analysis and propose some models with great value . Traditionally , there are two kinds of sequence analysis tools : alignment and alignment free models .

生物基因组序列分析表明，它是一个基因超家族。

Sequence analysis of genomes has revealed that P450 is a gene super-family .

基于时间序列理论方法的生物序列特征分析

Analysis on the Characteristics of Biological Sequences Based on Time Series Theory Methods

近二十多年来，DNA和蛋白质序列的数学描述在研究生物序列的比较分析中的作用越来越大，并且与之相对应的数值特征及相似性分析也相继提出。

Over the past two decades , the mathematical descriptions of DNA and protein sequences have made an increasingly important role in the comparative analysis of biological sequences analyze research , and the corresponding numerical characteristics and analysis of similar have also been brought forward one after another .

生物序列集成式分析平台的研制及其应用

Design and Develop of Compositive Sequence Analysis System and Its Application

基于网格的生物序列比对与分析系统

BioSA : System based on grid of genome sequence alignment and analysis

基于对齐的生物序列相似性分析

Alignment-based biological sequences similarity analysis

最长公共子序列在生物序列相似性分析、网络入侵检测、网络远程教学、电子商务、信息检索、数据挖掘、自动命题等领域应用广泛。

The longest common subsequence has been widely applying to many areas such as biological sequence similarity analysis , network intrusion detection , network remote instruction , E-commerce , information retrieval , data mining and automatic proposition .

本文在对传统的序列比对方法进行简要回顾的基础上，较系统地总结了已有的非比对方法并提出了一些新的非比对方法，然后针对一些具体的生物序列进行了分析研究。

In this dissertation , we firstly simply review the alignment methods ; secondly relatively systematically summarize the alignment-free methods and propose some new alignment-free methods ; finally make the analysis for some species sequences using the novel methods .

本文以生物序列的比较与分析为背景，提出了RNA二级结构和蛋白质结构的新的表示方法，并且列举了新表示方法在生物序列的相似性分析问题的应用。

Based on the comparative analysis of biological sequences for background . We present a new representation for RNA and protein , with the new method , we enumerate the specific application of biological sequences comparison .

生物信息流中序列分析软件的设计与开发

Design and Development of DNA Sequence Analysis Software

另外，还展示了这些表示法在生物序列的相似性分析和构建进化树等问题上的具体应用。

And discussed concrete applications of these representation methods to analysis of similarity constructions of evolutionary tree problems of biological sequences , etc.

生物序列数据是最重要的生物数据之一，通过对生物序列的分析，我们可以发现物种的遗传规律、物种间的关系等。

The biological sequence is one of the most important biological data . We will find genetic rules and relations between species by analyzing the biological sequences .

生物序列数据作为生物数据最重要的数据之一，将数据挖掘技术应用于生物序列数据的分析处理是目前研究者们最关注的研究领域。

Biological data of biological sequence data as one of the most important data , the data mining in biological sequence data analysis and processing is currently the researchers are most concerned about the areas of research .