Skip over navigation

Course Offerings

Course Evaluation Results

Course Details

Spring 2008-2009
ELE 571  

Digital Neurocomputing

Sun-Yuan Kung

The course will cover machine learning techniques & bioinformatics applications. Machine learning techniques topics: a) adaptive techniques for feature selection & dimension reduction, b) unsupervised cluster discovery: K-means, SOFM, hierarchical clustering, c) supervised classifiers e.g. linear discriminant analysis (LDA), support vector machines, & d) kernel-based clustering/classification techniques. Genomic applications, e.g. disease analysis & drug discovery: a) molecular biology overview, b) genomic sequence analysis & applications, c) DNA microarray data analysis & applications, & d) systems biology applications.

Sample reading list:
Pierre Baldi and Søren Brunak, Bioinformatics : the machine learning approach, 2nd Edition
SY Kung, M.W. Mak, S.H. Lin, Biometric Authentication: A Machine Learning Approach (2004)
Bernhard Schölkopf, Koji Tsuda, Jean-Philippe Vert, Kernel methods in computational biology (2004)

Other Requirements:
Not Open to Freshmen.

Other information:
The grade will be based on course projects.

Website:  http://http://www.blackboard.princeton.edu

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
42401 S01 9:30 am - 10:50 am M W   Engineering Quad B-Wing   B418   Enrolled:3 Limit:16