Data Handling in Biology--the application of computational and analytical methods to biological problems--is a rapidly evolving scientific discipline. Written in a clear, engaging style, Large Scale Data Handling in Biology is for scientists and students who are learning computational approaches to biology. The book covers the data storage system, computational approaches to biological problems, an introduction to workflow systems, data mining, data visualization, and tips for tailoring existing data analysis software to individual research needs.

1. What to Do with All the Data?
2. Data Storage, Backup and Archiving Architecture
   1. Organization of HCS Informatics Infrastructure
   2. Hardware and Network Infrastructure
   3. Do we need robust Data Movers (DM) in High Content Screening for data-flow automation
3. Workflow Systems
   1. Why is a workflow system important
   2. Visualization in workflow systems
   3. Architecture of workflow systems
   4. Public Domain Workflow Systems
   5. Commercial Workflow Systems
   6. Summary and Vision
4. Database Development: Laboratory Information Management Systems and Public Databases
   1. What Type of HCS Data Have to Be Managed in the Database
   2. Database Schema
   3. LIMS Architecture
   4. LIMS and User Management System
   5. Type of Users
   6. Integration and Public Databases
5. References