Fall Graduate Courses Offered
The following graduate courses offered this fall may be of interest to IPG students. Feel free to contact individual faculty members for more information.
Plant Genetics and Molecular Biology Instructors: Kathy Newton and John Walker Days and Time: T, Tr from 10:00-11:30 a.m. Location: 322 Tucker Hall BIO_SC 8300 Class #: 28540 |
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Molecular Biology of Plant Growth and Development Instructors: Mannie Liscum and Tom Guilfoyle Days and Time: M,F from 11:00-12:30 pm Location: 107 LSC BIO-SCI or BIOCHM 9468-01 Class #: 25110 (BioSci) or 10458 (Biochm) |
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Molecular Plant Physiology Instructors: Mannie Liscum and Gary Stacey Day and Time: M,W,F from 10:00-10:50 a.m. Location: 8 Tucker Hal BIO_SC or PLANT_SC 7320-01 Class #: 12715 (BioSci) or 10998 (PlantSci) |
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Analytical Spectroscopy: Mass Spectroscopy Instructor: Michael Greenlief Day and Time: M,W,F from 10:00-10:50 a.m. Location: 201 Schlundt Hall CHEM 8250 Class #: 15824 |
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Computational Methods in Bioinformatics Instructor: Toni Kazic Day and Time: M, W from 1:00-2:15 Location: 222 Eng. Bldg. West CS/INFOINST 7010 |
Course Description This course will cover algorithms used in bioinformatics, with an emphasis on phrasing biological problems so that they are amenable to computational solution; appropriate choice of computational strategies; and the algorithms used for particular biological problems. Students are expected to independently complete a research project that has some small novelty in bioinformatics and involves programming. Biologists who have taken this course previously learned to write Perl for their projects. |
Computational Systems Biology Instructor: Toni Kazic Day and Time: M, W from 3:00-4:15 Location: 112 Geological Sciences CS 8001 |
Course Description This is a seminar in the literature and will cover theories and methods in the modelling and analysis of large-scale, parallel physiology experiments such as microarrays, proteomics, and metabolomics experiments. Topics include the inference of causal relations from experimental data and reverse engineering of cells and cellular systems. Papers range from the early work of Stuart Kauffman and John Tyson to contemporary work on high-throughput experiments and metabolic engineering. |