Today is Wednesday, Dec. 11, 2019

Department of

Graduate Programs in Biomedical Informatics

Graduate Certificate applications accepted on a rolling basis

Core Courses

BE 7022 – Introduction to Biostatistics (3 credit hours)
Students will learn basic statistics such as mean, median, mode, standard deviation, variance, etc. Topics include probability, parametric statistics such as t tests and one way analysis of variance, and nonparametric statistics including both Wilcoxon tests and Kaplan-Meier estimation of survival. Bayes theorem, discrete (e.g. Binomial) and continuous probability distributions (e.g. normal distributions and one variable regression and product moment correlation and rank correlation are covered.


BMIN 7003 – Biomedical Informatics Seminar (1 credit hour)
The student will be expected to attend a weekly seminar in the areas of medical, clinical and bio-informatics, as well as general computer science topics related to biomedical research. A mix of research talks available from College of Engineering and Applied Science, College of Medicine, and Cincinnati Children’s Hospital and Medical Center can be used to satisfy the requirements of this seminar course.


BMIN 7053 – Introduction to Medical Informatics (3 credit hours)
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 7099 – Introduction to Bioinformatics (3 credit hours)
Introduction to Bioinformatics is a multidisciplinary, entry level graduate 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 complex structure and function, and 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.

Data Management (select one course)
EECE 6010 – Database Management (3 credit hours)
Database formal architectures emphasizing modeling and theory. Formal methods for database architectures; relational, hierarchical, object, object-relational and network; data dependencies, normalization, integrity constraints, concurrency, heterogeneous systems.


BE/PH 8093 – Introduction to Database Management Systems (3 credit hours)
This course emphasizes on hands-on experience of developing and using databases. Students will learn basic concepts of database techniques, use SQL to develop relational databases (with MySQL) and use NoSQL to develop non-relational databases (with CouchDB), and develop database applications to solve practical problems in biomedical science with big data. The course is highly interactive. Students will be trained to write R code in the classroom to interact with databases and perform data analyses.

 

Biomedical Informatics Grad Certificate Curriculum 2019-2020