Graduate Certificate in Clinical Bioinformatics

University of Toledo

Learning Outcomes

1) Apply clinical bioinformatics theories, methods and tools related to personal health, health care, public health, and biomedical research (for example): a) Work with and evaluate electronic health records, b) Work with and evaluate national health databases, c) Work with and evaluate omics repositories, d) Integrate clinical and omics data.

2) Describe analytic tools associated with systems/bioinformatic approaches, including (for example): a) Transcriptomics – microarray analysis vs. deep sequencing, b) Proteomic mass spectroscopic methods (identification and abundance), c) Determination and structure of interaction networks, d) Functional network maps.

3) Apply Intelligent Data Analysis Techniques including (for example): a) Dimension reduction techniques, b) Heuristic search techniques, c) Intelligent interfacing techniques.

4) Describe application of bioinformatic methods to clinical problems, by demonstrating understanding of: a) Biomarker discovery and validation, b) Major diseases such as cancer, diabetes, cardiovascular, and autoimmunity.