MS in Bioinformatics: A Concentration in Translational Medicine

Goal

To train physician-scientists who will be leaders in applying and stimulating the development of post-genomic technologies to clinical research and the practice of medicine.

Requirements

The master’s degree requires a total of 32 credits. MS candidates must demonstrate mastery of the core subject matter (no lower than a “B” in core courses) and complete a masters research project with a written and oral report which will serve as a masters thesis. Candidates will be expected to develop their ideas to the point of publication.

Core Courses

ENG BF 501: Bioinformatics Research Participation in a research project under the direction of a faculty advisor.  (2-4 credits)

ENG BF 527: Bioinformatics Applications This course explores the use of bioinformatics databases and software as research tools. Students will use data mining tools to extract DNA and protein sequences from primary and secondary databases. Software tools will be used to compare and analyze these sequences and construct gene and protein models for solving research problems related to molecular evolution, drug discovery, and genetic bases for development and diseases. (4 credits)

ENG BE 562: Computational Biology: Genomes, Networks, Evolution The algorithmic and machine learning foundations of computational biology, combining theory with practice are covered. Principles of algorithm design and core methods in computational biology, and an introduction of important problems in computational biology. Hands-on experience analyzing large-scale biological data sets.  (4 credits)

GRS MA 681: Accelerated Introduction to Statistical Methods for Quantitative Research Introduction to statistical methods relevant to research in the computational sciences. Core topics include probability theory, estimation theory, hypothesis testing, linear models, GLMs, and experimental design. Emphasis on developing a firm conceptual understanding of the statistical paradigm through data analyses.  (4 credits)

ENG BF 752: Legal & Ethical Issues of Science & Technology This course addresses the ethical, legal, and scientific aspects of 21st century genetics. As part of the new technologies, individuals, families, and society as a whole will have to make increasingly difficult decisions that affect us all. Students will analyze cases, question the legal system’s role in regulating the field, and discuss options for present and likely future challenges. Topics include gene therapy, DNA forensics, new reproductive techniques, biotechnology and patenting, transplantation, clinical research, and laboratory ethics. Students participate in a once-weekly discussion class, complete regular online homework assignments and write an opinion paper. (4 credits)

ENG BE 768: Biological Database Analysis Describes relational data models and database management systems; teaches the theories and techniques of constructing relational databases to store various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Introduces relational database query language SQL and the ORACLE database management system, with an emphasis on answering biologically important questions. Summarizes currently existing biological databases. Describes Web based programming tools to make databases accessible. Addresses questions in data integration and security. The future directions for biological database development are also discussed. (4 credits)

ENG BF 778: Physical Chemistry for Systems Biology This course introduces students to quantitative modeling in bioinformatics and systems biology. First, basic principles of statistical thermodynamics and chemical kinetics are discussed, with selected applications in biomolecular systems. Next, molecular driving forces in biology, and computation with biomolecular structures, are described. Finally, selected quantitative models of biomolecular networks are discussed. Students complete several homework assignments and programming projects. (4 credits)

ENG BF 831: Translational Bioinformatics Seminar Students will examine, discuss and evaluate recent papers that directly illustrate the use of bioinformatics either in pre-clinical or clinical research settings. Papers will be drawn from high-impact journals and students will take turns presenting the papers to the class and provide a critical review of each, both orally and in writing. They will also complete a research proposal directed to the goal of using bioinformatics to advance a medical procedure – either diagnostic or therapeutic. (2 credits)