Program and faculty
Bioinformatics and Computational Biomedicine deals with the analysis, handling, and comprehension of the large amounts of data produced by advanced techniques used in modern biological research (especially genomics, proteomics, and molecular and cellular biology).
The Division of Bioinformatics & Computational Biomedicine within the Department of Medical Informatics and Clinical Epidemiology (DMICE) provides a unified academic home for an array of disparate educational programs, inter-linked activities and collaborative research efforts across OHSU and beyond. The interdisciplinary coursework draws on inter-institutional faculty expertise at Portland State University and OHSU, and is synergistic with work in the Department of Public Health & Preventive Medicine, the Knight Cancer Institute, the Oregon Clinical and Translational Research Institute (OCTRI), and the Kaiser Center for Health Research.
Our bioinformatics track offers a rigorous, interdisciplinary submersion in statistics, algorithms, research methods, biology, and computation, with special attention paid to the areas that these competencies overlap (i.e. computational biology). Students are thus given the knowledge and skills to become successful researchers and analysts within the field of bioinformatics.
Dr. Shannon McWeeney Functional Genomics, Statistical Genetics, Systems Biology, Imaging
Dr. Eilis Boudreau Computational Neuroscience, Imaging
Dr. Aaron Cohen Text Mining, Information Retrieval, NLP
Dr. Arie Baratt Mathematical Modeling, Proteomics
Dr. Beth Wilmot Functional Genomics, Statistical Genetics
Dr. Guanming Wu Systems Biology, Databases, Probabilistic Graphical Models
Dr. Christina Zheng Functional Genomics, Data Reproducibility, Next Generation Sequencing
Dr. Michael Mooney Scientific Programming, Complex Trait Genomics, Machine Learning
Dr. Kemal Sönmez Functional Genomics, Systems Biology
Bioinformatics has become increasingly algorithmic and quantitative, in particular in the area known as computational biology. The primary goal of Master’s program in bioinformatics is to provide students with a rigorous grounding in the tools needed to successfully address current problems in the field. Students are thus given the knowledge and skills to become successful researchers and analysts within the field of bioinformatics.
The master's program consists of the following core curriculum:
- Bioinformatics and computational biomedicine
- Biomedical sciences
- Analytics and Biostatistics
- Computer science.
Graduation requirements: the Master of Science curriculum consists of 55 credits, divided between 43 credits of coursework and 12 credits of thesis work. The Master of Science - Non-Thesis replaces the master's thesis with a capstone project/publishable manuscript (for postdocs) or an internship experience where the student gains real-world experience in an operational setting, such as a healthcare organization or a company.
The mission of the Biomedical Informatics PhD program is to develop independent researchers, dedicated teachers and imaginative leaders in healthcare, academia, and industry. The development of leaders who can bring novel strategies and new ideas to the interdisciplinary domain of biomedical informatics is also a high priority objective.
The PhD program consists of the following core curriculum:
• Core Knowledge of Bioinformatics and Computational Biomedicine
• Doctoral Symposium
• Analytics and Biostatistics
• Mentored Teaching
• Advanced Research Methods
• Cognate Area of Study
A minimum of 135 credits are required for graduation. The section below details the distribution of credits. There will be a residency requirement of 12 - 15 credits for six consecutive terms in accordance with the by-laws of the School of Medicine Graduate Council.
Distribution of credits
Demonstration of Bioinformatics and Computational Biomedicine Knowledge: 43 credits minimum of subject courses required. Students with a background in certain areas (e.g., medicine or computer science) may substitute other courses but still must complete minimum 43 credits.
Reading and Conference: 10 credits minimum
Advanced Research Methods: 12 credits minimum; coherent set of courses beyond research methods minimum of master’s program.
Cognate Area: 12 credits minimum; cohesive set of courses to demonstrate depth in a cognate area in biomedical informatics.
Symposium: 3 credits minimum
Mentored Teaching Prep and Mentored Teaching: 8 credits minimum (2 x 4 credits per sequence)
Research and Dissertation: 48 credits