The Cancer Genome Atlas, a new genome project for cancer, presents numerous algorithmic, machine learning, and modeling challenges. We will examine in this context new and classic problems in computational biology including: genome assembly, genome rearrangements, phylogeny, and cellular interaction networks.
CSCI 1810 is recommended
PhD: Area "B" (Algorithms)
ScM: " Theory " or "Practice" course. (Depending on final project chosen.)
A critial reading of the literature requires engagement in the discussions of papers. Students are expected to contribute to class discussions by asking questions, making observations, identifying strengths and weaknesses, etc.
You will critically analyze the papers in the reading list. Critical reading of technical papers is a must-have skill in research. You will write a review summarizing the contributions of the paper, assess its weaknesses, and suggest further research areas or alternative approaches. Reports for three papers (approximately 2 pages each) and must be distributed between the three major topics of the course. Each review will be worth 10% of your grade.
Each student will be make one or two presentations from the reading list (the number depends on class size). A week before the presentation, the participant will email the instructor a detailed outline of the presentation. Similarly, the talk slides will be submitted at least two days before the presentation. The outline and slides should be modified on the basis of feedback before the presentation. After the presentation, a page summary (html) will be made for the benefit of future students.
Completion of either two half-semester or one full semester (with a midterm report) project(s) are required. Based on the background and interests of the student, the project can be theory, practice, or a combination of the two. Examples include: