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Department of

Graduate Programs in Biomedical Informatics

PhD Program Deadlines:
December 1 (non-binding early action)
February 15 (general admission)

Core Courses

BMIN 7053 - Introduction to Medical Informatics
Biomedical Informatics is an interdisciplinary field that combines knowledge of information sciences and medical sciences to optimize the use and application of biomedical data across the spectrum from molecules to individuals to populations. This course will present students with an introduction to the field of biomedical informatics through the use of core technologies and data science (computational and analytical methods) as it applies to clinical research and the use of health information technology to improve patient outcomes/healthcare delivery. Specific topics will include: overview of the field, data standards; security, confidentiality, regional health information exchange, standards, terminologies, database principles, data marts/data warehouses, interfaces and other topic as related to the healthcare and research setting. Learning objectives will be achieved using a variety of methods including: didactic lectures, group discussions, demonstrations, self-study, student projects, and selected readings from peer reviewed journal articles for each topic to develop critical analysis skills and ascertain real world applications.

BMIN 7054 - Data Science for Biomedical Research
Data Science for Biomedical Research will cover statistical and data mining techniques that are essential for processing, analyzing and mining Big Data, with the overarching goal of learning from data in order to gain useful predictions and insights.

BMIN 7099 - Introduction to Bioinformatics
Introduction to Bioinformatics is a multidisciplinary, entry level graduate course, which is an extension of current BME643 course and aims at achieving a deeper understanding of central algorithmic problems and current computational methods used in the context of data rich biomedical research. Subjects covered include: deep sequencing, biological sequence analysis, statistical models for gene expression profiling, prediction of protein and macromolecular complexes structure and function, systems biology. Analysis of algorithmic aspects will be accompanied by projects and case studies to provide a direct illustration of computational issues and to provide knowledge and practical command of standard bioinformatic tools and protocols that are being used to analyze complex biological data.

BMIN 8001 - Biomedical Informatics Practicum
The Biomedical Informatics Practicum is a project oriented course that combines the use of electronic medical records and other clinical informatics systems with research questions centered on Omics studies, personalized and preventive medicine, and quality of health care delivery. The projects will be designed to use state-of-the-art techniques and up to date data sets to identify current challenges develop solutions.

BMIN 8089 - Dissertation Research
Research tasks as advised by the dissertation adviser shall be completed.

GNTD 7003 - Ethics in Research
This course introduces students to ethical theories generally and the ethical and regulatory issues they are likely to encounter as researchers. Students will learn to identify issues, how to analyze ethical issues in research, and to develop coherent justifications for their ethical and responsible conduct of research.

GNTD 8001C - Introduction to Functional Genomics
This course consists of lectures/seminars on the theory and use of functional genomics approaches in biomedical research. Each lecture is accompanied by a lab session in an electronic classroom that provides hands-on experience in practical application of functional genomics principles. A key part of the course is group research projects in which students analyze primary genomics data to answer research questions.

Biomedical Informatics PhD Curriculum 2019-2020