Course Description : In recent years, there has been a explosion in the amount of biological information available due to technology developed by efforts such as the Human Genome Project. Bioinformatics is the field that includes the development and implementation of mathematical and computer techniques to analyze this data. In this course, the fundamental mathematical and algorithmic theory behind current bioinformatics techniques will be taught. The student will implement these methods. They include hidden Markov models, the dynamic programming algorithm, genetic algorithms, simulted annealing, neural networks, and information theory. The biological background will be provided in the course.
Grading Policy: The course grade will be determined as follows-
90-100 A
80-89.9 B
Problem Sets - 60%
70-79.9 C
Final Projects - 40%
0-69.9 F
Problem sets will be assigned as homework several times during the
semester. They will be due two weeks after they are assigned. The assingments
will be posted on the course web page. Late homeworks will not be
accepted.
All students are expected to complete the final project and make a presentation at the announced time.
Academic Honesty Policy : Academic dishonesty will not be tolerated. This includes cheating, plagiarism, and falsification of academic records. That being said, you can help each other out on the homework (this does not mean that you can copy each other's homework).
Important Dates: Thursday, April 11, 8:30 PM- Final Project Proposals
Due
Thursday, May 2, 8:30 pm -Final Project Presentations
Sage Advice: If you want to do well in course: 1) Do all the
problem sets. 2) Read the text book and any other assigned reading. 3)
Ask questions in class and office hours. 3) If you are having difficulty
doing the problem sets, be sure to get help. I encourage the students
discussing the course material and problems, but require everyone to do
the work - NO COPYING.