Master of Professional Studies in Bioinformatics and Computational Biology, In Person (MPBC)
The Science Academy, housed in the College of Computer, Mathematical, and Natural Sciences (CMNS), draws on the university’s collective expertise to provide academic programs that are both rigorous and relevant. Science Academy Graduate Programs translate research into applied knowledge and provides current and future professionals with invaluable skills.
Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students should contact the contact the program director, Amy Chester via email: scienceacademy@umd.edu.
Overview
The Master of Professional Studies in Bioinformatics and Computational Biology, In Person (MPBC) is a 30-credit, 10-course non-thesis graduate program that provides an education in the theory and practice of the major current areas in the field including problem contexts, mathematical and statistical foundations, computational approaches, communication, and ethical, privacy and legal considerations.
- Students acquire the skills and knowledge necessary to identify, choose, describe, explain, and apply bioinformatics and computational biology methods to problems in biology and biomedical research.
- Curriculum also covers relevant probability and statistics, data structures and algorithms, and machine learning.
- Designed for working professionals, requirements include 8 core courses and 2 electives.
- Successful graduates should be able to interpret, infer, and communicate results of bioinformatics and computational biology analyses to different audiences, with consideration of ethical, privacy, and legal issues.
- Can be completed in sixteen months of continuous full-time enrollment. Part-time enrollment is welcome. See Designation of Full-time/Part-time Status.
Courses
Below is a listing of all program courses. For a detailed course description that includes pre-requisites or co-requisites, see The Graduate School Catalog, Course Listing as follows: BIOI Course Descriptions (Coming soon).
| Type | Course Number | Title |
|---|---|---|
| Core | BIOI601 | Probability and Statistics |
| Core | BIOI602 | Principles of Data Science |
| Core | BIOI603 | Principles of Machine Learning |
| Core | BIOI604 | Principles of Molecular Biology, Genetics, and Genomics |
| Core | BIOI605 | Data Sources and Data Management in Bioinformatics |
| Core | BIOI606 | Sequence and Alignment |
| Core | BIOI607 | Data Structures and Algorithms for Bioinformatics |
| Elective | BIOI610 | Genome Annotation |
| Core | BIOI611 | Analysis of Gene Expression Data |
| Elective | BIOI621 | Genome Assembly and Annotation |
| Elective | BIOI699 | Capstone Research |
Registration Overview
- See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director.
- Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite.
- In addition, elective courses in Data Science & Analytics or Machine Learning may be available.
- Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit.
- The program uses specific section codes for registration, which are listed on the sample plan of study.
Sample Plan, Full-Time
| Semester | Year | Course Number | Section Code | Credits |
|---|---|---|---|---|
| Fall | 1 | BIOI601 | PCS* | 3 |
| Fall | 1 | BIOI602 | PCS* | 3 |
| Fall | 1 | BIOI604 | PCS* | 3 |
| Spring | 1 | BIOI605 | PCS* | 3 |
| Spring | 1 | BIOI606 | PCS* | 3 |
| Spring | 1 | BIOI607 | PCS* | 3 |
| Summer | 1 | BIOI610 | PCS* | 3 |
| Fall | 2 | BIOI603 | PCS* | 3 |
| Fall | 2 | BIOI611 | PCS* | 3 |
| Fall | 2 | BIOI621 | PCS* | 3 |
Sample Plan, Part-Time
| Semester | Year | Course Number | Section Code | Credits |
|---|---|---|---|---|
| Fall | 1 | BIOI601 | PCS* | 3 |
| Fall | 1 | BIOI604 | PCS* | 3 |
| Spring | 1 | BIOI605 | PCS* | 3 |
| Spring | 1 | BIOI606 | PCS* | 3 |
| Summer | 1 | BIOI610 | PCS* | 3 |
| Fall | 2 | BIOI602 | PCS* | 3 |
| Fall | 2 | BIOI611 | PCS* | 3 |
| Spring | 2 | BIOI603 | PCS* | 3 |
| Spring | 2 | BIOI607 | PCS* | 3 |
| Fall | 3 | BIOI621 | PCS* | 3 |
In-Person Learning
- Classes meet in UMD College Park campus classrooms, offering a focused, distraction-free learning environment.
- Classes are held weekday evenings (e.g., after 5:00 p.m.) to accommodate the working professional’s schedule.
- Uses the semester academic calendar with classes held in the fall and spring semester (16 weeks each).
- Instruction provided by University of Maryland faculty and professionals in the field. Includes instructors from several departments across campus, including Computer Science, Biology, Cell Biology and Molecular Genetics, Mathematics, and Electrical and Computer Engineering.
- Instructors present dynamic and interactive seminar-style instruction.
- Students enrolled in a program that features in-person instruction are required to submit the University’s Immunization Record Form prior to the first day of their first semester/term. See Health Requirements.
Upon successful completion, graduates will have mastered the following competencies:
- Explain multiple problem-solving methods in bioinformatics and computational biology.
- Apply bioinformatics and computational biology methods to problems in biology and biomedical research.
- Interpret and infer results of bioinformatics and computational biology analyses to different audiences.
- Communicate results of analyses with considerations of ethical, privacy and legal issues.