Independent Studies in Computational Biology

Aims and Objectives

Students gain the experimental and computational knowledge necessary to embrace a systems biology approach, and experience authentic systems genetics research by designing and conducting independent research projects with guidance from Center faculty, staff and postdoctoral associates.

By the end of this course, students will be able to:

  • analyze scientific literature
  • summarize primary research and review articles
  • explain the purpose, methods and results of a scientific article
  • develop questions and hypotheses around a specific area of research
  • describe methods for answering research questions
  • demonstrate understanding of statistical genetics
  • demonstrate understanding of measures of gene expression
  • demonstrate understanding of quantitative trait locus (QTL) analysis
  • plan and execute a research strategy
  • write or alter existing R code to perform specific tasks
  • locate data from bioinformatics resources
  • apply QTL analysis methods to phenotype and expression data
  • report analysis results in both written and oral forms
  • demonstrate an appreciation for education and careers in computational biology

Course Website