BIOCB 6010

Introduction to Computational Biology

Course Description

Course information provided by the Courses of Study 2024-2025. Courses of Study 2024-2025 is scheduled to publish mid-June.

This class is designed to inspire students in the life sciences to see the power of Computational Biology in advancing fundamental research. The course will initially be team taught by experts in diverse applications of Computational Biology, with each sharing the excitement of making clear to students how the introduction of computational approaches has been transformative in their field. The course will also teach many fundamental skills in manipulating large data sets, including genome sequences, functional genomic data, images, protein structures, etc.. The course will consist of two lectures each week and one practical exercise session each week. In the practicals, students will learn the use of many of the latest software tools, and will develop some basic programming skills. Students will learn essential problem solving skills in several aspects of genome analysis, and modeling in neurobiology, ecology, physiology and evolution. This will prepare them for future courses in these more focused biological areas covering specific applications of computer programming as well as use of specialized software tools. Students will be able to explore their own specific interests in greater depth on a term project.

When Offered Fall.

• Formulate succinct and focused research questions that make effective use of computation in diverse problems in ecology, genomics, physiology and neuroscience.
• Organize complex data structures in formats appropriate for analysis.
• Write short computer programs that organize data into formats that are readable by a wide variety of software.
• Apply appropriate analysis to data collected in these diverse fields.
• Identify software resources for tackling novel problems that you have never encountered before.
• Implement those software tools.
• Validate results and be critical in assessing their validity and generality.

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