Uniformed Services University of the Health Sciences
4301 Jones Bridge Road
Bethesda, Maryland 20814-4799
Phone: (301) 295-2163
FAX: (301) 295-3585
Pamela Cross, Secretary
The Biomedical Informatics Department is located on the ground floor of the main campus, around the corner from the Security Office that's accessible from the USU parking garage tunnel entrance.
Through our Research and Education Partnership with the National Library of Medicine and ongoing collaboration with each of the Armed Services, the Defense Health Agency, and the Veteran's Administration we have forged ahead in planning a future "Master of Biomedical Informatics (MBI)" degree program with clinical informatics track. Our program, once approved, will be delivered through distributive learning technologies to federal employees (uniformed and civilian). The MBI will be a professional degree designed to prepare medical department officers and federal employees for assignment as a Chief Medical Information Officers (CMIOs), Chief Nursing Information Officers (CNIOs), Chief Health Informatics (CHIs), or similar position. Our MBI program will prepare physician students for board certification in the subspecialty of clinical informatics. Our MBI program and pertinent details will be released soon and a progress blog will be created to update you on key steps. During this development/transition period, when we are building new courses, our USU on-site class offerings will be limited to our Bioinformatics Series.
USU On-Site Bioinformatics Series: This series will be taught by Associate Professor Robert Williams, PhD. All interested students should contact Dr. Williams in advance of course registration to discuss upcoming course offerings.
Introduction to Bioinformatics (MCB 904): The principle objective of bioinformatics is to find the relationships between DNA and protein sequence on the one hand, and biological function and disease on the other. Bioinformatics is the application of computer science and information technology to the field of biology and medicine. The goal of this course will be to give students overviews and practical application skills in the following topics: databases, sequence alignment, gene and regulatory sequence recognition, Perl, Bioperl, R, and Bioconductor programming, and Linux for Biologists. Students will be able to immediately start using these tools, or to move on to courses or tutorials at higher levels.
Perl Programming for Biologists (BID 504): The purpose of this course is to give students a practical working knowledge of the Perl programming language for applications in biology. Programming skills are becoming increasingly important in biology. From the text: "Advances in high-throughput biology have transformed modern biology into an incredibly data-rich science. Biologists who never thought they needed computer programming skills are now finding that using an Excel spreadsheet is simply not enough." Perl is the most widely used language used for biological problems, there is a very large number of existing Perl programs that can readily be adapted for repeated tasks typically performed by biologists, so it is seldom necessary for biologists to write perl programs from scratch, and "regular expressions" in Perl are applicable in a wide variety of other scripting languages, including Python.
Applied Statistics for Life Sciences using R (BID 505): The purpose of this course is to give students in the life sciences, epidemiology, biology, and psychology, a practical working knowledge of statistical programming using R. R is a tool designed for statistical analysis and extended to include many of the other tasks necessary for the analysis of statistical data, including data mining, high throughput analysis, neural networks, and other algorithms for pattern analysis. Students are expected to have an introductory understanding of statistics. Emphasis will be placed on a practical application of R to data taken from the literature and made available in the R packages for the disciplines represented by students in the class. The first part of this course will cover the use of R in statistical analysis in general. Students will subsequently be tracked into specialized topics in their own fields of study.
Unix and Databases for Biologists (BID 506): The purpose of this course is to give students a practical working knowledge of Unix (Linux and MacOS command line) and SQL databases. From Dudley JT, Butte AJ, 2009 A Quick Guide for Developing Effective Bioinformatics Programming Skills. PLoS Comput Biol 5(12): e1000589. doi:10.1371/journal.pcbi.1000589 -----: Bioinformatics programming skills are becoming a necessity across many facets of biology and medicine, owed in part to the continuing explosion of biological data aggregation and the complexity and scale of questions now being addressed through modern bioinformatics. Although many are now receiving formal training in bioinformatics through various university degree and certificate programs, this training is often focused strongly on bioinformatics methodology, leaving many important and practical aspects of bioinformatics to self-education and experience.
Python Programming for Biologists (BID 507): The purpose of this course is to give students a practical working knowledge of the Python 2.7 programming language for applications in biology. Programming skills are becoming increasingly important in biology and many biologists are finding that web based applications are not adequate for processing high throughput data or for tasks that require repeated operations. Python is now one of the scripting languages of choice for bioinformaticists. It is easy to learn and used, and can interface with Java, R, and other languages easily. While Perl may be a better choice for writing small programs that get work done, and for re-using code written by others, Python is preferred by many bioinformatics programmers who need to write larger programs.