CSC2431: Topics in Computational Biology
Computational Methods in Medicine

Winter 2016


Classes: F 10-12 in Rosebrugh 310

Instructor: Michael Brudno
Office: Pratt (PT) 286C
Office Hours: By appointment

Announcements

General information

Course Description: coming soon

The prerequisite is an undergraduate-level understanding of Computer Science. While I do not expect that you would have familiarity with all computational concepts we discuss, you should be able to quickly "catch up" on the relevant topics. Solid understanding of artificial intelligence (especially machine learning), algorithms, and basic statistical concepts (e.g. p-values, multiple testing correction) will be needed for for multiple parts of the course

Grading:
The basic requirements for the class will be a course project (60% of the grade), paper presentations and participation (20% of the grade) and written paper summaries (20% of the grade).

Syllabus & Readings

Will be posted to the Google group.

Writing paper summaries

Each person taking the class for credit is responsible for submitting a one page summary of the assigned papers before every class. The system for grading them will be a simple check-off, so no need to sweat too much. From the writeup I am looking for evidence that you read the papers and thought about them. Some evidence of this would be, for example, talking about the weaknesses of the paper (the strengths are in the abstract). The writeup need not be long. It is supposed to be evidence that you've done the work, not work in itself. If you are presenting a paper, you do not have to do a writeup for that paper, but should do the writeups for other papers being discussed that week.

The whole point of the paper summaries is to make sure that you've read the papers before coming to class, so no late summaries will be accepted.

Administrative details:

The class will satisfy group 4 (Human-Centric and Interdisciplinary Computing) breadth, as well as the Computational Biology group breadth.