To accommodate the significant diversity of backgrounds and goals of students in the CMB program, its requirements are deliberately flexible. In addition to the graduation requirements imposed by the student's host department and by the University of Washington Graduate School, the CMB program expects all students to complete the requirements described below. Students who fulfill these requirements will receive the CMB certificate.
As described more fully below, all CMB students will be required to complete the core CMB course, participate in the CMB journal club, attend the Combi seminar series, do at least one lab rotation, and complete a capstone project. Students will also be required to satisfy any remaining CMB prerequisites. These requirements are in addition to the Ph.D. requirements of the host department.
Each student will choose a CMB advisor from among participating faculty, preferably during the first year. The CMB advisor may or may not be the thesis advisor. Usually the CMB advisor will be in the student's host department, but cross-disciplinary and co-advising arrangements are common and encouraged. The host department will be responsible for administering appropriate examinations and awarding the degree.
A minimum of 15 credits must be completed. New: All 15 credits may now overlap with credits used toward your doctorate. This is easily attained by registering for Combi Seminar (Genome 521) the CMB Journal Club (CSE 590C), and research credits with CMB faculty, in addition to the required core course (Genome 541) and one elective. Other course combinations can also work. Program assistant Brian Giebel can help you determine which courses to apply toward this requirement.
The core required CMB course is either Genome 541 or CSE 527.
Genome 541 is a one-quarter overview course that is team taught by five CMB faculty members each year, typically during spring quarter. The course is arranged into two-week modules that cover a variety of topics in computational molecular biology. The specific topics vary annually but typically include molecular evolution, protein structure analysis, regulatory networks, etc.
CSE 527 introduces computational methods based on artificial intelligence (AI) and machine learning (ML) techniques for understanding biological systems and improving health care. AI/ML techniques such as explainable and interpretable ML, deep neural network learning, probabilistic graphical models, causal inference, and deep learning techniques are covered. Problem areas such as genetics, epigenomics, expression data analysis, proteomics, and electric health record data analysis are covered.
One CMB elective, selected from the list below.
Either a short-term lab rotation or research project is required. Ideally, the rotation or research project should involve input from a CMB faculty member other than (or in addition to) the student's primary thesis advisor. Completion of this requirement can be indicated by email confirmation from the student's project advisor.
Lab rotation: This type of rotation should involve exposure to wet lab work, either involving actual experiments in the lab or a "shadowing" component where the student observes lab work and then helps to analyze the resulting data. Wet lab rotations may be mentored by faculty who are not affiliated with CMB.
Research project: This type of project involves significant computational research. Students may provide a paper submitted to preprint servers, conferences, or journals on a topic relevant to computational biology with a CMB faculty member.
The CMB journal club is CSE 590C, a weekly seminar on Readings and Research in Computational Biology offered every autumn, winter, and spring. A minimum of one quarter is required for the CMB certificate. In this seminar, senior students mentor beginning students by working together on presentations.
The CMB seminar series is the weekly COMBI seminar, offered every autumn and winter. This series features research presentations by outside speakers as well as by participating CMB faculty. The latter is a primary mechanism by which students become familiar with the available potential research areas prior to choosing a thesis advisor. A minimum of one quarter is required for the CMB certificate (you need not necessarily register - simply attending is sufficient).
All students complete a capstone project under the supervision of CMB faculty and present the project to the CMB community. This presentation may take place at the CMB symposium, or it can take place at another time of your choice, such as at your dissertation defense, as long as the event is advertised to the CMB community by sending an announcement to compbio-seminars [ a t ] cs.washington.edu. The capstone project may be a component of your thesis research or a separate project if you choose. Completion of this requirement can be indicated by email confirmation from the student's thesis advisor.
Once you have completed program requirements, please contact Brian Giebel (bgiebel [ a t ] uw.edu) so that this certificate may be added to your transcript. Let Brian know which courses you took to complete program requirements.
The following list summarizes a wide variety of courses of potential interest to CMB students.
Note that not all courses are offered every year and that some have enrollment limitations. For more detailed information on individual courses, consult the University time schedule, individual course web pages, and/or the instructor.
AMATH 522: Computational Modeling of Biological Systems
AMATH 523: Mathematical Analysis in Biology and Medicine
AMATH 531: Mathematical Theory of Cellular Dynamics
AMATH 532: Mathematics of Genome Analysis and Molecular Modeling
BIOC 530: Advanced Biochemistry
BIOEN 423/CSE 486/EE 423 Introduction to Synthetic Biology
BIOEN 424/CSE 487/EE 424 Advanced Systems and Synthetic Biology
BIOEN 488/588 Computational Protein Design
BIOEN 523/CSE 586/EE 523 Introduction to Synthetic Biology
BIOEN 524/CSE 587/EE 524 Advanced Systems and Synthetic Biology
BIOEN 537 Computational Systems Biology
Computer Science and Engineering
CSE 427: Computational Biology
CSE 428: Computational Biology Capstone
CSE 527: Computational Biology
CSE 486/BIOEN 423/EE 423 Introduction to Synthetic Biology
CSE 487/BIOEN 424/EE 424 Advanced Systems and Synthetic Biology
CSE 546: Machine Learning
CSE 547: Machine Learning for Big Data
CSE 586/BIOEN 523/EE 523 Introduction to Synthetic Biology
CSE 587/BIOEN 524/EE 524 Advanced Systems and Synthetic Biology
GENOME 540 Introduction to Computational Molecular Biology: Genome and Protein Sequence Analysis
GENOME 569 Bioinformatics Workflows for High-Throughput Sequencing Experiments
CONJ 549: Microbial Population Biology
STAT 535 - Statistical Machine Learning
STAT 538 - Statistical Learning: Modeling, Prediction, and Computing
Statistical Genetics core courses, including the following:
BIOSTAT/STAT 550 Statistical Genetics I: Mendelian Traits
BIOSTAT/STAT 551 Statistical Genetics II: Quantitative Traits
BIOSTAT/STAT 552 Statistical Genetics III: Design and Analysis in Medical Genetics Studies
Additional Computational Courses at UW:
Genome 373 (for undergraduates)
Genome 559 (for those with little or no programming experience - not for students in the CMB program)