Textbooks

• Required: An Introduction to Bioinformatics Algorithms (by Neil C. Jones and Pavel A. Pevzner) Amazon pointer
• Recommended : Probabilistic Models of Proteins and Nucleic Acids ( by Richard Durbin , Sean R. Eddy , Anders Krogh , Graeme Mitchison ) Amazon pointer

Prerequisites

Format

The course is lecture-based with regular problem sets and machine problem assignments plus a midterm examination and final examination.

Course Policy and Grading

1. Attendance

Attendance is mandatory, but use common sense if you are sick or have other constraints. Note that attending the lectures is sometimes the only chance for you to learn certain materials as they may not necessarily be in the textbook.



2. Assignments

The assignments are designed to ensure that students have a deep and precise understanding of the major algorithms, thus the students are required to complete them independently. However, discussion with others is allowed to the extent of helping understand the material. The course newsgroup may be a good place for discussions. The purpose of student collaboration is to facilitate learning, not to circumvent it. The actual solution must be done by each student alone, and the student should be ready to reproduce their solution upon request. If any substantial discussion happens, every one involved must write down the names of the people that he/she has discussed with and the nature or topic of discussion. In any case, you must exercise academic integrity. See the University Policy on Academic Integrity, especially the section on plagiarism.

Late submission of an assignment would result in a reduced grade for the assignment, unless an extension has been granted by the instructor. An assignment is worth full credit at the beginning of class on the due date (later if an extension has been granted). It is worth at most 80% credit after that time unless an extension has been approved by the instructor. No homework will be accepted more than 3 days after the due date unless an extension has been approved by the instructor.



3. The optional extra "1 hour" project

Graduate students who take the course for full credit (i.e., 4 graduate hours) are required to finish a small project, which could be either a literature review on a bioinformatics topic or some piece of research work in bioinformatics. Team work is allowed. Students who plan to do such a project should discuss the plan with the instructor early in the semester. The project report is due on Dec. 15, Friday.



4. Grading

Grading will be based on the following weighting scheme.

• Assignments: 45%
• Midterm: 25%
• Final: 30%