ESSENTIAL COMPUTING SKILLS FOR BIOLOGIST

by Ziling Wang, Lishu Zhang

Overview

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.

Product Details

ISBN-13:	9781848169265
Publisher:	World Scientific Publishing Europe Ltd / Higher Education Press, China
Publication date:	07/02/2018
Series:	SERIES ON ADV IN BIOINFOR & COMPUTATIONAL BIOLOGY , #11
Sold by:	Barnes & Noble
Format:	eBook
Pages:	304
File size:	13 MB
Note:	This product may take a few minutes to download.

Table of Contents

Part I Databases and Bioinformatics Tools

Chapter 1 Online Sequence Database 3

1.1 Nucleic Acid Sequence Database 3

1.2 Protein Database 14

1.3 Protein Three-Dimensional Structure Database PDB 20

1.4 Genome Browser 20

References 28

Chapter 2 Sequence Alignment 30

2.1 Pairwise Sequence Alignment 30

2.2 Multiple Sequence Alignment 37

2.3 Basic Local Alignment Search Tool 41

References 50

Chapter 3 Molecular Phylogeny and Evolution 52

3.1 Introduction to Molecular Evolution 52

3.2 Models of DNA and Amino Acid Substitution 55

3.3 Tree-Building Method 61

3.4 Evaluating Tree 73

3.5 Perspectives 74

References 74

Chapter 4 Predicting DNA and Protein Function from Sequence 79

4.1 DNA Sequence Analysis 80

4.2 Protein Sequence Analysis 88

References 92

Chapter 5 Protein Structure 94

5.1 Overview of Protein Structure 94

5.2 Principles of Protein Structure 96

5.3 Protein Structure Prediction 100

5.4 Protein Structure Determining and Analysis 104

References 106

Part II Bioinformatics For Omics Data

Chapter 6 Human Genetic Variation and Human Disease 111

6.1 Human Genetic Variation 111

6.2 Human Disease 116

References 119

Chapter 7 Gene Expression Profiling with Microarray: Online Resources and Data Management 122

7.1 Microarray Data Analysis Software 123

7.2 Microarray Databases 125

7.3 Microarray Data Analysis 126

References 132

Chapter 8 Bioinformatics for Qualitative and Quantitative Proteomics 134

8.1 Protein Identification and Quantification from MS Raw Data 134

8.2 Proteomics Data Analysis 137

8.3 Proteomics Data Storage, Exchange and Sharing 143

References 147

Chapter 9 Bioinformatics for Metabolomics 152

9.1 Metabonomics and Metabolomics 152

9.2 Basic Approaches to Study Metabonomics 154

9.3 Data Analysis Methods 160

9.4 Metabonomics Databases 173

9.5 Summary 174

References 176

Chapter 10 Gene Ontology Database and KEGG Database 179

10.1 Gene Ontology Database 179

10.2 KEGG Database 184

References 191

Part III Statistics and Programming

Chapter 11 Basic Algorithms for Bioinformatics 195

11.1 Algorithms 195

11.2 Graph Theory 197

11.3 Dynamic Programming 206

11.4 Bayesian Statistics 214

11.5 Markov Models 221

11.6 Hidden Markov Model 229

11.7 Neural Networks 240

11.8 Clustering Analysis 248

11.9 Other Algorithms 260

11.10 Concluding Remarks 263

References 264

Chapter 12 An Introduction to R 270

12.1 What's R 270

12.2 How to Install R 271

12.3 RGui 273

12.4 How to Install R Extention Packages 276

12.5 Expressions and Assignments 278

12.6 Data Structure 278

12.7 Importing Data Into R 284

12.8 Exporting Data 286

12.9 Loops/Statements 286

12.10 Bioconductor 288

12.11 Further Resources 289

References 290

Index 292