Developing Bioinformatics Computer Skills

Bioinformatics — the application of computational and analytical methods to biological problems — is a rapidly evolving scientific discipline. Genome sequencing projects are producing vast amounts of biological data for many different organisms, and, increasingly, storing these data in public databases. Such biological databases are growing exponentially, along with the biological literature. It's impossible for even the most zealous researcher to stay on top of necessary information in the field without the aid of computer-based tools. Bioinformatics is all about building these tools.

Written in a clear, engaging style, Developing Bioinformatics Computer Skills is a thoughtful introduction to some of the most important topics in bioinformatics. It introduces and explains many popular software tools used in informatics research and covers the background theory that will help you understand how the tools are best used and why they are important.

Developing Bioinformatics Computer Skills covers:

• Setting up a bioinformatics workstation
• Unix for the working biologist
• Computational techniques for finding information in biological sequence, genome, and molecular structure databases
• Tools for identifying genes and detecting characteristic patterns that identify gene families
• Tools for modeling phylogenetic relationships, molecular structures, and biochemical properties
• Automatic data-handling and data-analysis processes
• Building databases
• Tools for data mining and data visualization

Whether you are a student who is learning computational approaches to biology for the first time or an experienced researcher who is just starting to use computers to handle your data, this book will help you develop a structured approach to biological data and a solid understanding of the tools you need to analyze it.

1. Introduction
1. Biology in the Computer Age
• How Is Computing Changing Biology?
•  Isn't Bioinformatics Just About Building Databases?
• What Does Informatics Mean to Biologists?
• What Challenges Does Biology Offer Computer Scientists?
• What Skills Should a Bioinformatician Have?
• Why Should Biologists Use Computers?
• How Can I Configure a PC to Do Bioinformatics Research?
• What Information and Software Are Available?
• Can I Learn a Programming Language Without Classes?
• How Can I Use Web Information?
• How Do I Understand Sequence Alignment Data?
• How Do I Write a Program to Align Two Biological Sequences?
• How Do I Predict Protein Structure from Sequence?
• What Questions Can Bioinformatics Answer?
2. Computational Approaches to Biological Questions
• Molecular Biology's Central Dogma
• What Biologists Model
• Why Biologists Model
• Computational Methods Covered in This Book
• A Computational Biology Experiment
2. The Bioinformatics Workstation
3. Setting Up Your Workstation
• Working on a Unix System
•  Setting Up a Linux Workstation
• How to Get Software Working
• What Software Is Needed?
4. Files and Directories in Unix
• Filesystem Basics
• Commands for Working with Directories and Files
• Working in a Multiuser Environment
5. Working on a Unix System
• The Unix Shell
• Issuing Commands on a Unix System
• Viewing and Editing Files
• Transformations and Filters
• File Statistics and Comparisons
• The Language of Regular Expressions
• Unix Shell Scripts
• Communicating with Other Computers
• Playing Nicely with Others in a Shared Environment
3. Tools for Bioinformatics
6. Biological Research on the Web
• Using Search Engines
• Finding Scientific Articles
• The Public Biological Databases
• Searching Biological Databases
• Depositing Data into the Public Databases
• Finding Software
• Judging the Quality of Information
7. Sequence Analysis, Pairwise Alignment, and Database Searching
• Chemical Composition of Biomolecules
• Composition of DNA and RNA
• Watson and Crick Solve the Structure of DNA
• Development of DNA Sequencing Methods
• Genefinders and Feature Detection in DNA
• DNA Translation
• Pairwise Sequence Comparison
• Sequence Queries Against Biological Databases
• Multifunctional Tools for Sequence Analysis
8. Multiple Sequence Alignments, Trees, and Profiles
• The Morphological to the Molecular
• Multiple Sequence Alignment
• Phylogenetic Analysis
• Profiles and Motifs
9. Visualizing Protein Structures and Computing Structural Properties
• A Word About Protein Structure Data
• The Chemistry of Proteins
• Web-Based Protein Structure Tools
• Structure Visualization
• Structure Classification
• Structural Alignment
• Structure Analysis
• Solvent Accessibility and Interactions
• Computing Physicochemical Properties
• Structure Optimization
• Protein Resource Databases
• Putting It All Together
10. Predicting Protein Structure and Function from Sequence
• Determining the Structures of Proteins
• Predicting the Structures of Proteins
•  From 3D to 1D
• Feature Detection in Protein Sequences
• Secondary Structure Prediction
• Threading
• Predicting 3D Structure
• Putting It All Together: A Protein Modeling Project
• Summary
11. Tools for Genomics and Proteomics
• From Sequencing Genes to Sequencing Genomes
• Sequence Assembly
• Accessing Genome Informationon the Web
• Annotating and Analyzing Whole Genome Sequences
• Functional Genomics: New Data Analysis Challenges
• Proteomics
• Biochemical Pathway Databases
• Modeling Kinetics and Physiology
• Summary
4. Databases and Visualization
12. Automating Data Analysis with Perl
• Why Perl?
• Pattern Matching and Regular Expressions
• Parsing BLAST Output Using Perl
• Applying Perl to Bioinformatics
13. Building Biological Databases
• Types of Databases
• Database Software
• Introduction to SQL
• Installing the MySQL DBMS
• Database Design
• Developing Web-Based Software That Interacts with Databases
14. Visualization and Data Mining
• Preparing Your Data
• Viewing Graphics
• Sequence Data Visualization
• Networks and Pathway Visualization
• Working with Numerical Data
• Visualization: Summary
• Data Mining and Biological Information

• Bibliography

A very good overview of the subject, even though the book could be called too simplistic (but considering the state-of-the-art in bioinformatics, it may be too advanced).