Class Description
CSE 549 will cover commonly used machine learning algorithms and their applications to computational biology. The class is structured so that problem motivates the application of the methods. Problems are divided into sections according to corresponding types of data: sequence, matrix, graphs, and 3D structure. In each of the sections problems will be described, then example machine learning method used to solve the problem will be discussed. We will learn about entropy, relative entropy, and mutual information in the context of solving DNA-binding site identification; learn about mixture models in the context of finding nucleosome positions; learn about graph structure learning in context of gene network construction; learn about graph searching in context of biomolecule searching; learn about feature selection in biomarker discovery; and feature extraction in context of protein searching. The class will involve combination of book & slides to describe the problems and machine learning methods and paper reading to see how it is actually applied. There will be a midterm exam and a semester project of your choosing.
Instructor
Assistant Professor
Sael Lee
Office: Academic Bldg. 428
Email: sael at sunykorea dot ac dot korea
Phone: +82 (32) 626-1215
Meeting time
Mon/Wed 09:00~10:20 Academic Bldg. 227
Office Hours
Wed. 16:00-18:00 (or send email for appointments)
Prerequisites
NA
TextBook
Required:
Additional:
Grading
Midterm: 40 %
Final Project: 60%
Assignments
The final project will not be limited to topics in computational biology, but will require you to apply methods and ideas that have been discussed in class. (proposal 20% + report 30% + presentation 10% = 60%)
