CAP 6545: Machine Learning in Bioinformatics

 

 

Lecture: MW 4:30PM - 5:45PM

Location: ENG 383

Instructor: Dr. Haiyan Hu

Email: haihu@cs.ucf.edu

Office: HEC- 233

Phone Number: 407-882-0134

Office Hours:MW 11:30AM - 12:30PM

 

 

Description:

In this class, we will provide an overview of the machine learning methods and their applications in Bioinformatics. Also, we will outline some research problems that may motivate the further development of machine learning tools for biological data analysis.

Bioinformatics is an active and interdisciplinary research area. This course is open to all students with background such as computer science, biology, mathematics or statistics who are interested in bioinformatics research.

 

 

Prerequisite:

No formal prerequisite and open to all graduate students.

 

 

Homeworks:

Reading of classic papers

A class project related to machine learning in bioinformatics.

 

Grading:

Paper presentation (30%), assignments (15%) final project presentation and report (55%)

 

Primary Schedule:

Date Topic Notes and Readings*
W1: 01/07 Introduction/Administrivia Notes; Readings;
01/09 Bioinformatics overview I Notes;
W2: 01/14 Bioinformatics overview II Notes;
01/16 Machine Learning Foundations: the Probabilistic Fr amework Notes;
W3: 01/21 No Class Martin Luther King Jr. Day
01/23 Machine Learning Foundations: the Probabilistic Framework Notes;
W4: 01/28 Probabilistic Modeling and Inference Notes; Readings; Readings;
01/30 EM Notes;
W5: 02/04 EM Applications Notes;
02/06 Hidden Markov Models Notes;
W6: 02/11 Hidden Markov Models applications Notes;
02/13 Hidden Markov Models applications Notes; Readings;Readings;Readings; Readings;
W7: 02/18 Hidden Markov Models applications Notes; Readings;Readings; Readings;
02/20 Support Vector Machine Notes;
W8: 02/25 Support Vector Machine applications Readings; Readings;
02/27 Support Vector Machine applications Readings; Readings;

W9

No Class Spring Break
W10: 03/11 Support Vector Machine applications

Notes; Readings; Readings;

03/13 Bayesian Network Notes; Readings; Readings;
W11: 03/18 Bayesian Network applications Notes;
03/20 Bayesian Network applications Notes;
W12: 03/25 Bayesian Network applications Notes; Readings;
03/27 Bayesian Network applications Notes; Readings;
W13: 04/01 Boosting and Bagging Notes
04/03 Boosting and Bagging applications Notes
W14: 04/08 Final project presentation and discussion
04/10 Final project presentation and discussion
W15: 04/15 Final project presentation and discussion
04/17 Final project presentation and discussion
W16: 04/22 Final project presentation and discussion

* Lecture notes will be put on the website before each class. Reading material is subject to change.