Topics in Computational Biology: Genomes, Networks, and Cancer (CSCI2950-C)

Fall 2007

Tuesday/Thursday 2:30-3:20pm [CIT 506]

Professor: Ben Raphael

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.

Course Organization

The course will be organized in seminar style where students will present recent papers on the topics listed below. Each topic will be introduced with background lectures. Students will undertake either two half-semester or one full semester (with a midterm report) project(s) to further study one of the class topics. The project could range from theoretical (e.g. designing a new algorithm and proving its correctness), to the practical (a software implementation) depending on the interest of the student.

Topics

Introduction -- The Cancer Genome Atlas
Cancer Genomes: Experimental Assays and Computational Methods
Models of Cancer Progression and Evolutionary Dynamics
Genome Assembly
Genome Rearrangement and Phylogeny
Protein and Regulatory Interaction Networks

Prerequisites

CSCI 1810 is recommended

Schedule

Course Credits (tentative)

PhD: Area "B" (Algorithms)
ScM: " Theory " or "Practice" course. (Depending on final project chosen.)
Significant Programming can be arranged with an appropriate class project

Grading

Participation (10%)

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.

Written reports (20%)

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.

Presentations (20%)

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.

Class Project(s) (50%)

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:

An implementation of one of the algorithms discussed in class with testing on new biological data.
Development of a new approach for a problem in computational biology.

During the term, students will turn in a written project proposal which will count towards part of the project grade. Further details to come.

Extra Credit (up to 10%)

Up to 5% extra credit can be earned twice for attending a computational biology seminar and writing a one page summary of the talk. Such credit MUST be approved by the instructor BEFORE the seminar.