From medicine to genomics to ecology, all fields of biology are now generating
large and complex datasets that can only be analyzed using computational
approaches. This course introduces computational techniques and perspectives
to biologists that are new to computational thinking. Students will learn how to
design research workflows, decompose complex problems into simpler solvable
units, and apply scientific computing principles to research. In addition, students
will practice foundational computing skills, such as using the UNIX
operating system on research clusters, writing custom analysis programs with
shell scripts and with Python, and summarizing and visualizing analysis output. The
laboratory exercises build on one another, culminating in the construction of a
bioinformatics pipeline that can process and analyze molecular data. Students
will apply their newly learned computational skills and use their pipeline to
analyze virus sequence evolution and explore evolutionary models. Prerequisites: Biol 2970; Math 132 (Calculus II);
Math 223 (Calculus III) or Math 2200 (Elementary Probability); CSE 131 (Computer Science I; suggested course).
Credit/no credit.
Course Attributes: FA NSM; AR NSM; AS NSM
