导语
内容提要
生物信息计算是在生命科学的研究中,以计算机为工具对生物信息进行储存、检索和分析的科学,是当今生命科学和自然科学的重大前沿领域之一。王字玲、张丽姝主编的《生物信息计算(英文版)(精)》重点集中在基因组学和蛋白质组学两方面,分12章介绍:序列数据资源及其检索、蛋白质序列数据库、序列比对与比对搜索、真核生物基因结构的预测分析、分子进化分析、蛋白质结构数据库和结构可视化、蛋白质结构与功能预测、微阵列数据分析、系统生物学网络结构分析等内容,并对Getle Ontology数据库、KEGG数据库及基因功能注释、R语言及Biocondnctor进行了简述和应用示例。
本书是计算机科学、生物信息学以及统计学的知识综合,可供相关领域的专业人员参考使用,也可用于生物学、计算机科学专业的教学。
目录
PART Ⅰ DATABASES AND BIOINFORMATICS TOOLS
Chapter 1 Online Sequence Database
1.1 Nucleic Acid Sequence Database
1.2 Protein Database
1.3 Protein Three-Dimensional Structure Database PDB
1.4 Genome Browser
References
Chapter 2 Sequence Alignment
2.1 Pairwise Sequence Alignment
2.2 Multiple Sequence Alignment
2.3 Basic Local Alignment Search Tool
References
Chapter 3 Molecular Phylogeny and Evolution
3.1 Introduction to Molecular Evolution
3.2 Models of DNA and Amino Acid Substitution
3.3 Tree-Building Method
3.4 Evaluating Tree
3.5 Perspectives
References
Chapter 4 Predicting DNA and Protein Function from Sequence
4.1 DNA Sequence Analysis
4.2 Protein Sequence Analysis
References
Chapter 5 Protein Structure
5.1 Overview of Protein Structure
5.2 Principles of Protein Structure
5.3 Protein Structure Prediction
5.4 Protein Structure Determining and Analysis
References
PART Ⅱ BIOINFORMATICS FOR OMICS DATA
Chapter 6 Human Genetic Variation and Human Disease
6.1 Human Genetic Variation
6.2 Human Disease
References
Chapter 7 Gene Expression Profiling with Microarray: Online Resources and Data Management
7.1 Microarray Data Analysis Software
7.2 Microarray Databases
7.3 Microarray Data Analysis
References
Chapter 8 Bioinformatics for Qualitative and Quantitative Proteomics
8.1 Protein Identification and Quantification from MS Raw Data
8.2 Proteomics Data Analysis
8.3 Proteomics Data Storage, Exchange and Sharing
References
Chapter 9 Bioinformatics for Metabolomics
9.1 Metabonomics and Metabolomics
9.2 Basic Approaches to Study Metabonomics
9.3 Data Analysis Methods
9.4 Metabonomics Databases
9.5 Summary
References
Chapter 10 Gene Ontology Database and KEGG Database
10.1 Gene Ontology Database
10.2 KEGG Database
References
PART Ⅲ STATISTICS AND PROGRAMMING
Chapter 11 Basic Algorithms for Bioinformatics
11.1 Algorithms
11.2 Graph Theory
11.3 Dynamic Programming
11.4 Bayesian Statistics
11.5 Markov Models
11.6 Hidden Markov Model
11.7 Neural Networks
11.8 Clustering Analysis
11.9 Other Algorithms
11.10 Concluding Remarks
References
Chapter 12 An Introduction to R
12.1 What's R
12.2 How to Install R
12.3 RGui
12.4 How to Install R Extention Packages
12.5 Expressions and Assignments
12.6 Data Structure
12.7 Importing Data Into R
12.8 Exporting Data
12.9 Loops/Statements
12.10 Bioconductor
12.11 Further Resources
References
Index