Introduction to Applied Computational Tools in Immunology

2 credits · Graduate

Introduction to computational tools for analyses of immunological data sets, including but not limited to single-cell data such as that from flow cytometry or CyTOF, Luminex, and genomic analyses. Students become familiar with major web-based databases and analysis suites for immunological and genomic data; gain a working knowledge of the major software/algorithms for working with major data types, and be able to apply at least one computational tool in these areas to analyze a public data set. Lectures will be followed by a demonstration and interaction session on the topic. Students will complete a computational analysis project and present it to the class. Undergraduate students must be approved by the instructor. Auditors allowed and must be approved by the instructor and the department.