The fundamentals of database modeling as used in bioinformatics. By the end of the course, students should be able to: understand different types of data models, know how hierarchical and relational models work and give examples that are widely used for biological databases, understand the capabilities of a standard, open source RDBMS, understand the tasks required for data integration and how to use SQL as a research tool. Introduction to ML, XML Schema, and BioOntologies as widely used data exchange and organization tools in bioinformatics databases.
Concepts and techniques of evaluating bioinformatics data. The objective of this course is to provide students with a working knowledge of data sources, current tools and methodologies used for bioinformatics research though a variety of hands-on data analysis activities.
Introduction of fundamentals of programming for bioinformatics (sometimes called “scripting”) using current programming languages and paradigms. Introduces both the language and the use of the language within a Unix environment, demonstrating how interpreted languages serve both as a useful tool for writing and testing programs interactively and as a powerful data analysis and processing tool for bioinformatics. Hands-on computing labs in which students learn bioinformatics computing and programming are also included.