ENG BF 527: Applications in Bioinformatics
The field of bioinformatics is concerned with the management and analysis of large biological datasets (such as the human genome) for the purpose of improving our understanding of complex living systems. This course introduces graduate students and upper-level undergraduate students to the core problems in bioinformatics, along with the databases and tools that have been developed to study them. Computer labs emphasize the acquisition of practical bioinformatics skills for use in student’s research. Familiarity with basic molecular biology is a prerequisite; no prior programming knowledge is assumed. Specific topics will include the analysis of biological sequences, structures, and networks. 4 cr.
ENG BF 528: Applications in Translational Bioinformatics
Bioinformatics is an interdisciplinary field devoted to managing and analyzing largescale biological data, such as the DNA sequence of the human genome, and has become an essential tool in interpreting and translating biological knowledge for use in a clinical setting. This course introduces graduate and upper–level undergraduate students to the principles of bioinformatic analysis applied to translational studies. Application topics will include gene expression analysis, biomarker development, and Genome Wide Association Studies (GWAS). Bioinformatics methods including microarray analysis, short read sequence analysis, biological pathways and geneset enrichment analysis, and Quantitative Trait Loci (QTL) will be covered. Lectures and assignments will be designed around reproducing the results of preselected studies from the literature that exemplify the topics. The primary focus will be using existing software tools and published data to perform analyses, but most tasks will require some programming. 4 cr.
ENG BF 550: Foundations of Programming, Data Analytics, and Machine Learning in Python
This course is for students trained in life sciences with minimal exposure to programming, statistics, and data analysis. The goal of the course is to develop both practical skills and theoretical foundations in handling data sets and developing simple computational solutions to problems arising in biomedical research. 4 cr.
ENG BF 751: Molecular Biology and Biochemistry for Bioinformatic
Modern research in the life sciences is an increasingly interdisciplinary endeavor where new fields of study have developed at the interfaces of biology, chemistry, physics, mathematics, and computer science. In many instances, the development of these new fields goes hand in hand with development of new experimental approaches to surveying the content of the cell. While, traditional molecular cell biology and biochemistry courses often focus on the basic details of cell physiology and macromolecular (DNA, lipid, protein) structures, they too often neglect the quantitative aspects of number, scale, forces, etc. that are crucial to providing a larger context within living systems. This course aims at reframing the basic concepts of cell and molecular biology in a quantitative context and providing a basic overview of some of the key approaches used to develop a quantitative framework inside the cell. How this detailed information can then be applied to bioinformatics research problems will also be explored. 4 cr.
ENG BE 768: Biological Database Systems
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 cr.
ENG BF 831: Translational Bioinformatics Seminar
After commencing briefly with general introductory material (published reviews and other relevant back-ground information), students will proceed to 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 such as Nature, Science, PNAS, Cell, and Science Translational Medicine. Students will take turns presenting the papers to the class and provide a critical review of each. They will also complete a term paper in the form of a research proposal directed to the goal of using bioinformatics to advance a medical intervention (e.g. prognostic, diagnostic or therapeutic). Brief guest presentations by researchers in BUSM laboratories will be arranged as appropriate. Previous guest facilitators have included faculty from the Department of Biostatistics, Section of Computational Biomedicine, and Department of Mathematics and Statistics as well as industry leaders. 2 cr.
ENG BF 541: Bioinformatics Internship
Each student must complete an internship with a minimum of 400 hours of on-the-job experience (e.g., 10 weeks full-time work in the summer). The format is very flexible, and part-time internships running concurrently with classes or employment are acceptable. While most internships will take place in industrial settings, suitable projects can also be carried out in non-profit or academic research laboratories. In every case the student must submit the MS Internship Approval from to the Program Director before commencing an internship. For this purpose, “bioinformatics” means extensive use of computational tools to analyze, display and/or archive biological information (usually at the molecular level). The project supervisor must be familiar with the tools employed, and if possible, the position should involve regular interaction with “wet-bench” scientists. 2 cr.