R. W. Doerge
Professor, Departments of Agronomy and Statistics, Purdue University
Director, Statistical Bioinformatics Center
Middleburgh Central, New York, 1982 Math Class.
B.S. in Mathematics, University of Utah , 1986.
M.Stat. in Mathematics, University of Utah, 1988.
Ph.D. in Statistics, North Carolina State University, 1993.
Postdoctoral Fellow in Department of Biometrics and Plant Breeding, Cornell University, 1995.
Address:
- 150 North University Street
Mathematical Sciences Building
Department of Statistics,
Purdue University
West Lafayette, IN 47907-1399, USA
- Office: 522, Mathematical Sciences Building
- Email:
doerge@stat.purdue.edu
- Phone: 765-494-6030
- Fax: 765-494-0558
Teaching:
-
FALL 2008 Bioinformatics Seminar Series Lectures (titles and abstracts) (ST598B)
- Day and Time: Tuesday; 4:30-5:30pm
- Location: Mechanical Engineering (ME) 161
- Details: This is a 1 credit course (ST598B), where attendence and participation determine your
grade outcome.
- Every registered student is allowed one excused (non-work related) absence.
- Although this is a seminar course, everyone is welcome to attend. Weekly e-mail announcements of the
seminars are mailed every Thursday (with reminders on Monday). If you would like to be added to the
Bioinformatics mailing list and/or suggest a speaker, please contact R.W. Doerge.
Research and Bio. :
Although my formal training is in Mathematics and Statistics, my research lies on the interdisciplinary boundaries of many fields (Animal
Science, Biology, Biochemistry, Botany, Chemistry, Computer Science, Horticulture, Genetics, Genomics, Plant Breeding, etc.) that are
currently involved in assessing genomic based questions. Statistical Genomics brings together all of these scientific disciplines into one
arena to ask, answer, and disseminate biologically interesting questions and information in the quest to
understand the ultimate function of DNA for each
and every genome. Currently, my research program encompasses four broad areas: development of methodology for genetic mapping and
quantitative trait loci (QTL) location; applying up to date genetic mapping and QTL methodology to real experimental data; assessing genetic
variation and diversity of populations and germplasm collections; and understanding and analyzing data from microarray based technologies for the purpose of
statistically designing and then testing genomic/biologically based questions.
R.W. Doerge Publications:
R.W. Doerge Students:
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