MEDS 4032 | 3 credit hours

Spring Semester | Syllabus (PDF)

TR 10:00 – 11:20 AM

Paul Rosevear, PhD | paul.rosevear@uc.edu | 513-558-3370

This course is a survey of the application and interpretation of high-throughput molecular biology methods (-OMIC technologies) used to produce high-volume biological data. The new 'omic' technologies allow the components of a living organism to be analyzed in their entirety and provide new insights into the complexities of organism function. Technologies covered include genomics, transcriptomics, proteomics, and metabolomics. Genomics and transcriptomics describe the structure and expression of the genome, proteomics provides information about the proteins expressed in cells under a certain set of conditions and metabolomics seeks to identify and quantify the diversity of metabolites and metabolic networks within an organism.

Key to understanding scientific and medical data resulting from applications of these technologies is an understanding of experimental design, data collection, analysis and interpretation. Relationships between the individual technologies will be explored and strategies for integrating –OMIC information will be discussed. In this course the student will learn how 'omics' technologies work and about aspects of experimental design, analysis and interpretation (bioinformatics). A series of case studies will be used to illustrate how these technologies engender a better understanding of complex biological systems and processes.

Learning Objectives

• Learn about the various –OMIC disciplines and the types information they provide the user
• Appreciate the –OMIC experiment from study design and sample preparation through data collection and analysis
• Gain a brief overview of the applications of these approaches in research and medicine
• Discuss the ethical issues in the use of –OMIC technologies including predisposition testing, sample storage and associated clinical data
• Understand and describe modern high-throughput molecular techniques used to produce high-volume biological data
• Understand computational biology methods for interpretation of data from high-throughput experiments
• Explore recent advances in the use of –OMIC methodologies in various diseases