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E-raamat: Essential Computing Skills For Biologists

(Beijing Jiaotong Univ, China), (Beijing Jiaotong Univ, China)
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This is a handbook of methods and protocols for biologists. It aimed at undergraduate, graduate students and researchers originally trained in biological or medical sciences who need to know how to access the data archives of genomes, proteins, metabolites, gene expression profiles and the questions these data and tools can answer. For each chapter, the conceptual and experimental background is provided, together with specific guidelines for handling raw data, including preprocessing and analysis.The content is structured into three parts. Part one introduces basic knowledge about popular bioinformatics tools, databases and web resources. Part two presents examples of omics bioinformatics applications. Part three provides basic statistical analysis skills and programming skills needed to handle and analyze omics datasets.
PART I DATABASES AND BIOINFORMATICS TOOLS
Chapter 1 Online Sequence Database
3(27)
1.1 Nucleic Acid Sequence Database
3(11)
1.2 Protein Database
14(6)
1.3 Protein Three-Dimensional Structure Database PDB
20(1)
1.4 Genome Browser
20(10)
References
28(2)
Chapter 2 Sequence Alignment
30(22)
2.1 Pairwise Sequence Alignment
30(7)
2.2 Multiple Sequence Alignment
37(4)
2.3 Basic Local Alignment Search Tool
41(11)
References
50(2)
Chapter 3 Molecular Phylogeny and Evolution
52(27)
3.1 Introduction to Molecular Evolution
52(3)
3.2 Models of DNA and Amino Acid Substitution
55(6)
3.3 Tree-Building Method
61(12)
3.4 Evaluating Tree
73(1)
3.5 Perspectives
74(5)
References
74(5)
Chapter 4 Predicting DNA and Protein Function from Sequence
79(15)
4.1 DNA Sequence Analysis
80(8)
4.2 Protein Sequence Analysis
88(6)
References
92(2)
Chapter 5 Protein Structure
94(17)
5.1 Overview of Protein Structure
94(2)
5.2 Principles of Protein Structure
96(4)
5.3 Protein Structure Prediction
100(4)
5.4 Protein Structure Determining and Analysis
104(7)
References
106(5)
PART II BIOINFORMATICS FOR OMICS DATA
Chapter 6 Human Genetic Variation and Human Disease
111(11)
6.1 Human Genetic Variation
111(5)
6.2 Human Disease
116(6)
References
119(3)
Chapter 7 Gene Expression Profiling with Microarray: Online Resources and Data Management
122(12)
7.1 Microarray Data Analysis Software
123(2)
7.2 Microarray Databases
125(1)
7.3 Microarray Data Analysis
126(8)
References
132(2)
Chapter 8 Bioinformatics for Qualitative and Quantitative Proteomics
134(18)
8.1 Protein Identification and Quantification from MS Raw Data
134(3)
8.2 Proteomics Data Analysis
137(6)
8.3 Proteomics Data Storage, Exchange and Sharing
143(9)
References
147(5)
Chapter 9 Bioinformatics for Metabolomics
152(27)
9.1 Metabonomics and Metabolomics
152(2)
9.2 Basic Approaches to Study Metabonomics
154(6)
9.3 Data Analysis Methods
160(13)
9.4 Metabonomics Databases
173(1)
9.5 Summary
174(5)
References
176(3)
Chapter 10 Gene Ontology Database and KEGG Database
179(16)
10.1 Gene Ontology Database
179(5)
10.2 KEGG Database
184(11)
References
191(4)
PART III STATISTICS AND PROGRAMMING
Chapter 11 Basic Algorithms for Bioinformatics
195(75)
11.1 Algorithms
195(2)
11.2 Graph Theory
197(9)
11.3 Dynamic Programming
206(8)
11.4 Bayesian Statistics
214(7)
11.5 Markov Models
221(8)
11.6 Hidden Markov Model
229(11)
11.7 Neural Networks
240(8)
11.8 Clustering Analysis
248(12)
11.9 Other Algorithms
260(3)
11.10 Concluding Remarks
263(7)
References
264(6)
Chapter 12 An Introduction to R
270(22)
12.1 What's R
270(1)
12.2 How to Install R
271(2)
12.3 RGui
273(3)
12.4 How to Install R Extention Packages
276(2)
12.5 Expressions and Assignments
278(1)
12.6 Data Structure
278(6)
12.7 Importing Data Into R
284(2)
12.8 Exporting Data
286(1)
12.9 Loops/Statements
286(2)
12.10 Bioconductor
288(1)
12.11 Further Resources
289(3)
References
290(2)
Index 292
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