前辅文
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