Problem Sets
Collaboration Policy: Students may discuss and work on problems in groups but must write up their own solutions, without using notes from group work. I.e., you can use the group to obtain understanding, but not to simply copy down solutions reached by the group. Please write the names of people with whom you collaborated on the problem set.
Late Policy: Each student has five free late days (calendar days) total for the class. For each late day beyond that, 20% will be deducted from the late assignment.
Project
October 13: Summary/Critique Reading List due
Each group submits a list of 3-4 papers on a coherent topic that they will review. The idea is that the information you learn while reading the papers and writing the critique should inform your choice of project, so you should be thinking about possible project topics when you select your papers. A good starting point for selecting papers and topics is the list of relevant papers on the course webpage. Some of these will be covered in class, but many won't.
October 17: Daphne approves of the reading list and/or suggests changes.
You are also invited to meet with or email Daphne prior to the October 13 deadline to consult about the reading list and avoid changes at this stage.
October 17-26: Meet with Daphne at least once to discuss project proposal
October 30: Summary/Critique due
The critique should consist of a report of approximately 10 pages, summarizing and critically reviewing the papers on your reading list. The report should show not just that you have read and understood the papers on your list, but also that you have thought in depth about issues surrounding them, such as:
October 30: Project proposal due
Each group must submit a written proposal of 1-2 pages for the class project. The project does not have to contain a large programming component. You are free to use existing tools (including but not restricted to those listed on the web site), provided you clearly describe what you did and cite them appropriately. You are also welcome to use existing software infrastructure like machine learning or statistical analysis code bases. The most important aspect of the project is that you should be able to perform a creative and interesting analysis of biological data, in the spirit of the material covered in the course, and draw appropriate conclusions. The project topic does not need to be totally original, but neither should it simply be a rehash of previous work. A good project might provide an interesting extension of work we will study in class or add a new twist to an existing method of data analysis. Even better would be a project that investigates a novel question or applies a new computational technique, but this is not required. Good examples for the kind of project we are looking can be found in the papers on the reading list for the class.
October 31: Daphne approves project proposals and/or suggests changes.
Due to the requirement of a meeting before the project proposals are due, we hope that only small changes are likely to be required.
December 8: Poster Session
Each group will present a poster describing their project at a class poster session. All group members must be present, and should be prepared to present the work and answer questions.
December 11: Project report due
The final written report for the class project is due by email. There is no length requirement, but a reasonable goal is 10-15 (single column, 12pt), with several figures illustrating the method and the results. Your report should clearly motivate the problem, describe the data and methods used, and present your results and conclusions. By and large, the report should look like one of the research papers on the reading list for the class (without generating new experimental data, of course).