Computational Biology, 2nd Edition
- Length: 493 pages
- Edition: 2
- Language: English
- Publisher: Springer
- Publication Date: 2013-01-31
- ISBN-10: 3642347487
- ISBN-13: 9783642347481
- Sales Rank: #3007186 (See Top 100 Books)
Computational Biology: A Practical Introduction to BioData Processing and Analysis with Linux, MySQL, and R
This greatly expanded 2nd edition provides a practical introduction to
- data processing with Linux tools and the programming languages AWK and Perl
- data management with the relational database system MySQL, and
- data analysis and visualization with the statistical computing environment R
for students and practitioners in the life sciences. Although written for beginners, experienced researchers in areas involving bioinformatics and computational biology may benefit from numerous tips and tricks that help to process, filter and format large datasets. Learning by doing is the basic concept of this book. Worked examples illustrate how to employ data processing and analysis techniques, e.g. for
- finding proteins potentially causing pathogenicity in bacteria,
- supporting the significance of BLAST with homology modeling, or
- detecting candidate proteins that may be redox-regulated, on the basis of their structure.
All the software tools and datasets used are freely available. One section is devoted to explaining setup and maintenance of Linux as an operating system independent virtual machine. The author’s experiences and knowledge gained from working and teaching in both academia and industry constitute the foundation for this practical approach.
Table of Contents
Part I Whetting Your Appetit
1 Introduction
2 Content of This Book
Part II Computer and Operating Systems
3 Unix/Linux
Part III Working with Linux
4 The First Touch
5 Working with Files
6 Remote Connections
7 Playing with Text and Data Files
8 Using the Shell
9 Installing BLAST and ClustalW
10 Shell Programming
11 Regular Expressions
12 Sed
Part IV Programming
13 AWK
14 Perl
15 Other Programming Languages
Part V Advanced Data Analysis
16 Relational Databases with MySQL
17 The Statistics Suite R
Part VI Worked Examples
18 Genomic Analysis of the Pathogenicity Factors from E. coli Strain O157:H7 and EHEC Strain O104:H4
19 Limits of BLAST and Homology Modeling
20 Virtual Sequencing of pUC18c
21 Querying for Potential Redox-Regulated Enzymes
Appendix A Supplementary Information