CAP 6938: Data Mining in Bioinformatics (Fall 2010) |
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Lecture: MW 4:30PM - 5:45PM Location: ENGR 0224 Instructor: Dr. Haiyan Nancy Hu Email: haihu@cs.ucf.edu Office: HEC- 233 Phone Number: 407-882-0134 Office Hours: MW3:00PM - 4:30PM
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Description: This course will summarize computational techniques for bridging two fields: data mining and bioinformatics, for successful mining of biological data. Recent progress in biology, medical science, bioinformatics, and biotechnology has led to the accumulation of tremendous amounts of biodata that demands in-depth analysis. On the other hand, recent progress in data mining research has led to the development of numerous efficient and scalable methods for mining interesting patterns in large databases. In this class, we will provide an overview of the data mining methods that help biodata analysis. Also, we will outline some research problems that may motivate the further development of data mining tools for the analysis of various kinds of biological data. 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.
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Prerequisite: No formal prerequisite and open to all graduate students.
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Book References: Data Mining : Concepts and Techniques, by Jiawei Han and Micheline Kamber, Elsevier, 2000.ISBN 1558604898.550 pages. Molecular Biology of the Cell, by Bruce Alberts et al., 4th edition, 2002.
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Grading: Assignments (20%). Paper presentation (20%). Each student will give a presentation of a course-related paper. Students are encouraged to discuss with the instructor to decide the topic he/she would like to present. Final project (60%). We may have students from very diverse background such as biology and computer science. Final problem-solving projects can be either biology-oriented or programming-oriented depending on a student's own background. Students are required to discuss with the instructor to design the final projects during the early weeks of the class. A student is encouraged to discuss with the instructor on collaborating with another student with different background on the final project. |
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Preliminary Schedule:
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