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Common Curriculum Offerings


Fall 2017 Offered


Deconstruction of Research. (3 credits) Deconstruction of Research is based on the premise that construction of new scientific knowledge builds from a foundation of primary evidence that requires critical evaluation through active analysis and productive discourse. Students will learn and understand the nature and development of scientific knowledge transmitted through oral and written avenues. Students will learn the necessary skills required for critical analysis of general concepts no matter how familiar or unfamiliar the topic.

Featured Faculty:

  • Murali Chandra, PhD - Integrative Physiology and Neuroscience
  • Ryan Driskell, PhD - School of Molecular Biosciences
  • Anthony Nicola, PhD - Immunology and Infection Diseases, Paul G. Allen School for Global Animal Health
  • Anders Omsland, PhD - Immunology and Infection Diseases, Paul G. Allen School for Global Animal Health
  • David Rossi, PhD - Integrative Physiology and Neuroscience
  • Joy Winuthayanon, PhD - School of Molecular Biosciences

Spring 2018 Scheduled


Topics in Biomedical Experimentation. 1 credit (may be repeated). This course examines the philosophy of experimental design and practical application and analysis of various experimental approaches in biomedical research. Each section (module) is independent of other sections and is taught within a 5 week block. There are three consecutive blocks per semester. The first 5 week block is always Philosophy of Experimental Design and is required of students from programs participating in the iPBS umbrella.

Philosophy of Experimental Design: This course will help graduate students develop an understanding and the habits of mind regarding acquisition of new knowledge through examining the philosophy and principles of experimental design and analysis.

Analysis of Biomedical Experiments: This course will inform the student of common misapplications of statistics in biomedical experimentation. Emphasis is on probabilistic decision making in life science data analysis, matching experimental goals with the correct statistical approaches, and common pitfalls in analysis. This course will not substitute for courses that teach formal statistical methods and computation.

Imaging & Image Analysis:  This course will guide students in the selection of optimal imaging techniques for the particular question they seek to answer, provide hands on experience with collecting results from a sample of their interest (or provided sample), and then once the image is collected, the optimal means to extract data from the image.  

Working with Proteins

Epidemiology:  Check back for new coursework offered in Vet_Path.