Solving modern biological problems requires advanced informatics and computational methods. Key techniques include database management, data modeling, pattern recognition, data mining, query processing and visualization of biological data. Until very recently, virtually all public databases were simply large flat files stored in simple format. Navigating among databases required expert knowledge and considerable patience. The huge quantities of biological data and escalating demands of modern biological research increasingly require the sophistication and power of information technology tools. More specifically, optimal use of these tools requires proximity information ? knowing which data points are in the surrounding area of others. In this book we will present methodologies and data structures for gathering high-quality approximations of biological information, and will use these information technologies as the foundation to develop practical tools for clustering and visualization in biological data mining and database management. TOC: 1) Intorduction to Bioinformatics 2) Bioinformatics Databases 3) Data Modeling and Simulation for Bioinformatics 4) Data Mining for Bioinformatics 5) Machine Learning and Pattern Matching for Bioinformatics 6) Visiualization of Biological Sequences 7) Bioinformatics Networking and Tools 8) Conclusion and Future Work