Bioinformatics is a highly interdisciplinary STEM field that integrates computational and statistical methods for analyzing large biological data sets. Bioinformaticians apply their biological and computational sciences backgrounds to develop, utilize, and optimize new computational tools for organizing, synthesizing, and analyzing the rapidly increasing amount of biological and biomedical data.
Prospective students choose between the Thesis-based track and the Non-thesis track.
THESIS-based track
Students will be trained and mentored in conducting independent hypothesis-driven research, including experimental design, data analysis, and interpretation of results. They will also learn scientific writing and presentation design and delivery. After graduation, students are primed for competitive Ph.D. programs and positions at research institutions, in government agencies and other public sectors, as well as in the private sector.
NON-THESIS Track
Students gain real-world experience in an internship environment and are exposed to a breadth of coursework in the field of bioinformatics. At the conclusion of their studies, graduates are competitive for employment in the biotech industry, as well as in bioinformatics positions in academia, government agencies, hospitals, and related public and private institutions.
CURRICULUM
Degree Requirements
Applicants pursuing the Master of Science in Bioinformatics select the Thesis-based track or the Non-Thesis track. Students must complete 30 credit hours. Six (6) courses, worth a total of 17 credit hours, comprise the Core Curriculum, and the remaining 13 credit hours will consist of track-specific courses.
Core Curriculum
Course List
| Code |
Title |
Hours |
| BIOL 488 | Bioinformatics | 3 |
| COMP 483 | Computational Biology | 4 |
| STAT 437 | Quantitative Bioinformatics | 3 |
| BIOI 500 | Advanced Bioinformatics | 3 |
| BIOI 501 | Bioinformatics Seminar | 1 |
| BIOI 565 | Exploring Proteins (Fall only) | 3 |
| or CHEM 465 | Special Topics in Biochemistry |
| Total Hours | 30 |
Track Specific Courses
Thesis Track
Course List
| Code |
Title |
Hours |
| UNIV 370 | Responsible Conduct in Research and Scholarship | 0 |
| BIOI 494 | Bioinformatics Research Design | 1 |
| BIOI 499 | Bioinformatics Research | 8 |
| BIOI 595 | Thesis Supervision | 1 |
| * | 3 |
| Total Hours | 13 |
* Thesis track: No stipulation regarding the department of the Bioinformatics Elective (see list below).
Non-Thesis Track
Course List
| Code |
Title |
Hours |
| BIOI 498 | Bioinformatics Internship | 1 |
| * | 12 |
| Total Hours | 13 |
* Non-Thesis Track: Bioinformatics Elective Courses must be selected from at least three departments.
Bioinformatics Electives
Course List
| Code |
Title |
Hours |
| BIOL 402 | Microbiology | 3 |
| BIOI 495 | Special Topics in Bioinformatics (Human Genetics) | 3 |
| BIOL 482 | Advanced Molec Genetics | 3 |
| BIOL 495 | Special Topics (Genomics - Spring only) | 3 |
| BIOL 495 | Special Topics (Human Molecular Genetics) | 3 |
| BIOL 495 | Special Topics (Metagenomics - Fall only) | 3 |
| CHEM 425 | Special Topics in Organic Chemistry (Medicinal Chemistry) | 3 |
| CHEM 435 | Special Topics in Physical Chemistry (Computational Biochemistry) | 3 |
| CHEM 455 | Special Topics in Analytical Chemistry (Introduction to Spectroscopy) | 3 |
| CHEM 465 | Special Topics in Biochemistry (Enzymology) | 3 |
| CHEM 465 | Special Topics in Biochemistry (Plant Biochemistry) | 3 |
| CHEM 465 | Special Topics in Biochemistry (Protein Crystallography) | 3 |
| COMP 406 | Data Mining | 3 |
| COMP 413 | Intermediate Object-Oriented Development | 3 |
| COMP 439 | Distributed Systems | 3 |
| COMP 460 | Algorithms & Complexity | 3 |
| COMP 453 | Database Programming | 3 |
| COMP 471 | Theory of Programming Languages | 3 |
| COMP 479 | Machine Learning | 3 |
| COMP 486 | Computational Neuroscience | 3 |
| STAT 406 | Stochastic Processes | 3 |
| STAT 407 | Statistical Design | 3 |
| STAT 408 | Applied Regression Analysis | 3 |
| STAT 410 | Categorical Data Analysis | 3 |
| STAT 436 | Topics in Biostatistics | 3 |
All PhD students and students in thesis-based Master's degree programs must successfully complete UNIV 370 Responsible Conduct in Research and Scholarship or other approved coursework in responsible conduct of research as part of the degree requirements. It is strongly recommended that students complete this two-day training before beginning the dissertation/thesis stage of the program.
Graduate & Professional Standards and Regulations
Students in graduate and professional programs can find their Academic Policies in Graduate and Professional Academic Standards and Regulations under their school. Any additional University Policies supercede school policies.
LEARNING OUTCOMES
In Loyola's M.S. in Bioinformatics program you will gain fundamental skills that will help you be an inquisitive scientist, including:
- a solid foundation in biological, computational, chemical, and statistical concepts and theory;
- the facility to interpret primary scientific literature;
- the capacity to employ statistical and computational methods to investigate and solve problems within the life sciences;
- the ability to conduct bioinformatics study in industry and/or the research environment; and
- science-related oral and written communication skills.
