This Area of Concentration is optional, yet the successful completion of these requirements will allow this concentration to be noted on your official transcript.

Area of Concentration Courses

Three of these courses are required to earn this Area of Concentration within the MS in Individualized Genomics and Health degree.

This course covers basic concepts and practical applications of modern laboratory diagnostic techniques. Topics include the principles of testing methodology, quality assurance, and the application of molecular methods to the clinical and research laboratory. The test methods to be covered include nucleic acid-based methods, such as hybridization, amplification, and sequencing, non-nucleic acid methods, such as HPLC, GLC, and protein analysis, and technologies such as PFGE, ribotyping, RFLP, and serological testing methodologies. In addition to the test procedures, students are exposed to aspects of statistics, quality control, and regulatory issues, as well as applications of these methods to the diagnosis and prognosis of human disease. Prerequisites: 410.601 Biochemistry, 410.602 Molecular Biology. SCI

This laboratory course introduces students to methods for manipulating and analyzing nucleic acids. Students gain extensive hands-on experience with plasmid purification, restriction mapping, ligations, bacterial transformations, gel electrophoresis, and applications of the polymerase chain reaction. This course is not recommended for students with substantial experience in these methodologies. Prerequisites: 410.602 Molecular Biology. SCI

The Advanced Recombinant DNA Laboratory course consists of integrated laboratory exercises designed to give students hands-on experience with various molecular techniques. This innovative hybrid course is intended for advanced learners with extensive molecular biology experience who want to use the current and emerging techniques commonly employed in government and industry. This course will review fundamental molecular biology research principles and summarize the process of converting a research-based laboratory into a clinical-level laboratory. The onsite laboratory learning experiences will include, but not be limited to, PCR optimization, quantitative real-time PCR, and control of gene expression by DNA sequencing in the clinical setup. The essential concepts discussed will include setting up a clinical lab, writing Standard Operating Protocols (SOPs) at the clinical level, and applying for a CLIA certificate. Students will also be introduced to microarray analysis and the utilization of bioinformatics pipelines. Students are required to attend the onsite laboratory period. Prerequisites: 410.601 Biochemistry; 410.602 Molecular Biology; 410.656 Recombinant DNA Laboratory; or consent of program committee. SCI

The recent revolution in DNA sequencing technologies has transformed biology within a few short years, decreasing the cost and difficulty of sequencing dramatically to the point where the “$1,000 human genome” is in sight. Armed with complete genome sequences, biologists need to identify the genes encoded within and the variation in these genes between individuals, assign functions to the genes, and put these into functional and metabolic pathways. This course will provide an overview of next-generation sequencing technologies in the historical context of DNA sequencing, the pros and cons of each technology, and the bioinformatics techniques used with this sequence information, beginning with quality control assessment, genome assembly, and annotation. Prerequisites: 410.602 Molecular Biology, 410.633 Introduction to Bioinformatics, 410.634 Practical Computer Concepts for Bioinformatics. SCI

This course will introduce students to various methods for analyzing and interpreting transcriptomics data generated from technologies such as oligonucleotides or two-channel microarrays, qRT-PCR, and RNA sequencing. Topics will include scaling/normalization, outlier analysis, and missing value imputation. Students will learn how to identify differentially expressed genes and correlate their expression with clinical outcomes such as disease activity or survival with relevant statistical tests; methods to control for multiple testing will also be presented. An introduction to linear and nonlinear dimensionality reduction methods and both supervised and unsupervised clustering and classification approaches will be provided. Open source tools and databases for biological interpretation of results will be introduced. Assignments and concepts will make use of publicly available datasets, and students will compute and visualize results using the statistical software R. Prerequisites: 410.601 Biochemistry, 410.602 Molecular Biology, 410.645 Biostatistics, 410.634 Practical Computer Concepts for Bioinformatics, or an undergraduate computer programming course. SCI

Students should be aware of state-specific information for online programs. For more information, please contact an admissions representative.

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