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Statistical Methods in Bioinformatics
UT course #: BIPG 5200/7200 - 3 cr
Prerequisites: PUBH532 - Statistical Methods I (or equivalent, or permission of course director)
Offered: Fall Semester, Tuesdays/Thursdays. Lectures posted online/Blackboard.
Course director: Dr. Sadik Khuder, Department of Medicine, (419) 383-6244, Sadik.Khuder@utoledo.edu
Summary: This course introduces students to statistical methods commonly used in bioinformatics, but which are not covered in depth in general introductory statistics courses. Students will learn to use statistical programs and related bioinformatics resources locally and over the internet. Lectures and lab discussion will emphasize on the statistical models and methods underlying the computational tools. The course will focus on the application of newer statistical methods and the reasoning behind these applications. Emphasis will be placed on the analysis of functional genomic experiments, and students will learn statistical techniques used to interpret microarray data. Specific course objectives include:
1. Have a strong understanding of fundamental concepts of the statistics that underlie bioinformatics;
2. Understand the formulation of stochastic models for genomic data;
3. Be able to apply statistical techniques to analyze microarray data and interpret the results generated;
4. Be able to use statistical tests commonly employed in bioinformatics;
5. Be familiar with statistical methods and software for solving complex problems in bioinformatics.
Grading: The course grade will be determined by performance on the weekly exercises (50%), semester project (20%), and final exam (30%).
Instruction: The course is primarily taught by the course director, with some lectures from other faculty at UT.
Text: Parmigiani, et al., The Analysis of Gene Expression Data, Springer, New York, 2003
Ewens & Grant, Statistical Methods in Bioinformatics, Springer, Verlag Press, New York, 2001
Link to course page for registered students: BIPG 5200/7200 Academic Intranet Page
Reference books (recommended):
Mount. Bioinformatics: Sequence and Genome Analysis, Cold Spring Harbor Laboratory Press, Cold Springs Harbor, New York, 2001.
Balding et al. Statistical Genetics, John Wiley Publishing Co, New York, 2001.
Gibson & Muse. A primer of Genomic Science, Sinauer, Massachusetts, 2002.
END-OF-COURSE STUDENT EVALUATION FORM: please click here
After completion of the Statistical Methods course, please click on the above link, print out the Evaluation Form, complete and return anonymously to:
Jo Anne Gray
3rd Floor CCE Building
Mail Stop: 1034