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RBIF 105

Proteomics: Analytical and Computational Principles

Proteomics constitute the parallel characterization of the set of proteins from an organism's genome. High-throughput, parallel study of proteins is invaluable to the discovery of modern medicines and diagnostics. This course covers emerging analytical techniques for the study of proteomes, as well as the computational needs that support them. Concepts addressed include the physicochemical and biological properties of proteins and their relationship to the genome; protein separation technologies; technologies for high throughput expression, isolation, and characterization of proteins; protein networks and protein-protein interactions; data management tools, data integration, and knowledge management.

At the end of the course, students will be able to:

Develop an appropriate research plan to answer questions in functional proteomics and biomarker discovery.

Develop familiarity with the laboratory techniques applied to the functional analysis of proteins and their interactions.

Use public proteome databases, computational analysis tools, and resources for proteomic research.

Assess the importance of proteome research in drug discovery.

Read and analyze scientific literature relating to proteomic research.

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