IGERT CURRICULUM
The Bioinformatics PhD curriculum consists of four parts:- Coursework -- The course requirements are flexible to accomodate differences in the backgrounds of our students. There are currently six core required courses plus a graduate seminar. Students are also expected to take several elective courses. IGERT Fellows are expected to take at least two elective courses in one or more of the following areas:
- biological networks
- biological systems
- probability
- statistics
- data mining
- Rotations -- Students work in a faculty members lab for a period of 8 to 10 weeks. This provides experience in doing a variety of bioinformatics research and aides students in finding a dissertation mentor
- Summer Wet Lab Experience -- This is designed to give our new students an extensive hands-on experience in a wet-lab collecting data. It consists of a two-month wet-lab immersion in the lab of one of our experimentalist faculty, where students will gain working knowledge of at least one of several high-throughput experimental techniques, including: microarrays, chromatin immunoprecipiation, quantitative RT-PCR, cloning, in situ hybridization, 2-D gels, mass spectrometry, and Western blotting. Organisms studied will include: bacteria, yeast, rodent and human cell cultures, fruitflys, Xenopus oocytes, and the starlet sea anemone Nematostella vectensis, among others.
This immersion will occur during the two months preceding the start of first-year classes, a time when students have no other responsibilities and can focus their efforts full-time in the lab. During the two months, students will work on experiments, attend lab meetings, and meet regularly with the faculty supervisor. During a weekly student seminar, students will discuss the techniques they are using, their successes, difficulties, and results. In addition, local outings will be organized for the students to help build camaraderie and ease their transition to graduate school.
- Challenge Project -- The Project extends over both semesters in the first year and is counted as a required course. Open-ended problems involve bioinformatics as a key element, typically requiring the use of large data sets and computational analyses to make predictions about molecular function, molecular interactions, regulation, etc. Projects are proposed by the program faculty and some of the projects build off problems addressed during the wet-lab experience. The projects are designed to have multi-year goals, allowing students further along to share their expertise and experience with the first year students.
Students work in teams of 4 with complementary backgrounds, e.g., undergraduate biology and computer science majors. Each team has a faculty supervisor, who serves as an advisor, not as a director of the research project. Teams are expected to generate and test ideas and are encouraged to seek out other program faculty for guidance and expertise. During the year, teams meet regularly in a Challenge Project Seminar. Besides acting as a forum for exchange of ideas, the seminar gives students an opportunity to develop their public speaking and presentation skills. An end-of-the-academic-year symposium will be held to present results and predictions.
The end result of the computational analysis phase of the project is a set of predictions, some of which can be validated retrospectively using data available through online sources or from program faculty labs. But, the goal is to produce new information and so some predictions will require experimental validation. During the last 2 months of the academic year, teams design feasible validation experiments in consultation with the experimentalist faculty.