Bioinformatics and Computational Biology (BCB)

www.bcb.iastate.edu
bioinformatics@iastate.edu
(Interdepartmental Graduate Major)
Supervisory Committee: D. Dobbs, Chair; D. Voytas, Assoc. Chair; A. Andreotti, D. Ashlock, V. Honavar, P. Schnable
Participating Faculty: R. Ackerman, S. Aluru, A. Andreotti, D. Ashlock, D.Berleant,
A. Bogdanove, V. Brendel, S. Carpenter,
A. Carriquiry, P. Chitnis, D. Cook, H-H. Chou, G. Culver, M. Daniels, J. Davidson, J. Dekker, J. Dekkers, J. Dickerson, P. Dixon, D. Dobbs, O. Eulenstein, D. Fernandez-Baca,
R. Fernando, X. Gu, M. Hargrove, K-M. Ho,
V. Honavar, R. Honzatko, F. Janzen, S. Kothari, S. Lamont, H. Levine, R. Maddux, J. Mayfield, L. Miller, W. A. Miller, C. Minion, J. Morris,
A. Myers, G. Naylor, D. Nettleton, N. Nilsen-Hamilton, T. Peterson, E. Pollak, A. Qamhiyah, J. Reecy, P. Reilly, S. Rodermel,
M. Rothschild, P. Schnable, R. Shoemaker,
J. Smith, H. Stern, C. Tuggle, D. Voytas,
J. Wendel, S. Willson, R. Wise, Z. Wu,
E. Wurtele

Undergraduate Study

Courses in bioinformatics and computational biology are offered for undergraduates, but a baccalaureate degree is not offered at this time.

Undergraduates wishing to prepare for graduate study in Bioinformatics and Computational Biology should obtain solid undergraduate training in at least one of the foundation disciplines: molecular biology, computer science, mathematics, statistics, and physics. Undergraduates should elect courses in basic biology, basic transmission and molecular genetics, chemistry, physics, mathematics at least through calculus, statistics, and computer programming.

Graduate Study

Work is offered for the master of science and doctor of philosophy degrees with a major in Bioinformatics and Computational Biology (BCB). Faculty are drawn from several departments: Agronomy; Animal Science; Biochemistry, Biophysics and Molecular Biology; Botany; Chemical Engineering; Computer Science; Electrical and Computer Engineering; Mathematics; Physics and Astronomy; Plant Pathology; Statistics; Veterinary Microbiology and Preventive Medicine; and Zoology and Genetics.

The BCB program emphasizes interdisciplinary training in six related areas of focus: Bioinformatics, Functional and Structural Genomics, Genome Evolution, Macromolecular Structure and Function, Mathematical Biology and Computational Modeling, and Metabolic and Developmental Networks. Additional information about research areas and individual faculty members is available at: www.bcb.iastate.edu.

BCB students are trained to develop an independent and creative approach to science through an integrative curriculum and thesis research projects that include both computational and biological components. First year students are appointed as research assistants and participate in BCB 697 (Graduate Research Rotation), working with three or more different research groups to gain experience in both "wet" (biological) and "dry" (computer) laboratory environments. In the second year, students initiate a thesis research project under the joint mentorship of two BCB faculty mentors, one from the biological sciences and one from the quantitative/computational sciences. The M.S. and Ph.D. degrees are usually completed in two and five years, respectively.

During the first year, all BCB students complete background coursework in calculus, molecular genetics, computer science, statistics and discrete structures, with specific courses determined by prior training. The total course requirements for Ph.D. students include one core course in Computational Molecular Biology (BCB 594), one core course in Molecular Genetics (e.g., Gen 511, BBMB 501), and at least 12 credits of advanced coursework in the areas of Molecular Biology (6 credits) and either Computer Science or Mathematics/Statistics (6 credits in one area). Students make research presentations (BCB 690), attend faculty research seminars (BCB 691), and participate in workshops/symposia (BCB 591). M.S. students take the above background and core courses, take at least 12 credits of advanced coursework, and may elect to participate in fewer seminars and workshops. Additional coursework may be selected to satisfy individual interests or recommendations of the Program of Study Committee. All graduate students are encouraged to teach as part of their training for an advanced degree. (For curriculum details and sample programs of study, see: www.bcb.iastate.edu.

Courses open for nonmajor graduate credit: 484, 495.

Courses Primarily for Undergraduate Students

BCB 484. Computational Mathematics for Biologists (Same as Math 484.)
(3-0) Cr. 3. F. A survey of graph theory, linear algebra, discrete math, and algorithms used in computational biology with examples taken from genomics, phylogenetics, and structure problems. This course provides mathematics background for BCB/Gen/Com S/Math 594. Nonmajor graduate credit.

BCB 495. Molecular Biology for Computational Scientists (Same as Gen 495.)
(3-0) Cr. 3. F. Dobbs. Survey of molecular cell biology and molecular genetics for nonbiologists, especially those interested in bioinformatics/computational biology. Basic cell structure and function; principles of molecular genetics; biosynthesis, structure, and function of DNA, RNA, and proteins; regulation of gene expression; selected topics. Provides biological background for BCB/Gen/Com S/Math 594. Nonmajor graduate credit. Credit for graduation will not be allowed for more than one of the following: Gen 411 and 495.

Courses Primarily for Graduate Students, Open to Qualified Undergraduate Students.

BCB 549. Advanced Algorithms in Computational Biology (Same as Cpr E 549, Com S 549.)
See Computer Engineering or Computer Science.

BCB 556. Computational Genomics and Evolution (Same as Gen 556.)
(3-0) Cr. 3. Prereq: Biol 301. Gu. Introduction to evolutionary sequence analysis at the genome level. Topics include sequence alignment, phylogenetic inference, molecular clock analysis, ancestral state inference, sequence/structure relation, functional divergence and prediction, evolutionary development, genome duplication, and comparative genomics. Focus will be on data analysis and biological interpretation.

BCB 590. Special Topics
Cr. var. Prereq: Permission of instructor.

BCB 593. Workshop in Bioinformatics and Computational Biology
(1-0) Cr. 1, each time taken. F.S. Current topics in bioinformatics and computational biology research. Lectures by off-campus experts. Students read background literature, attend preparatory seminars, attend all lectures, meet with lecturers.

BCB 594. Computational Molecular Biology (Same as Gen 594, Math 594, Com S 594.)
(3-0) Cr. 3. F.S. Prereq: Biol 301 and 302 or Math 304 and 307 (Math 317 may be used in place of 307) or Com S 311 and 330 or equivalent courses. Introduction to the biological background and the algorithms used in sequence comparison and data base search, fragment assembly and physical mapping of DNA, building of phylogenetic trees, analysis of genome rearrangement, and molecular structure prediction. Practice with some of the software commonly used for these problems.

BCB 596. Genomic Data Processing (Same as Gen 596, Com S 596.)
Cr. 3. Prereq: Com S 208 or 228, and Com S 311. Chou. Introduction to major computational methods relevant to modern molecular biol-ogy research. Topics include database construction, search and update; data collection and dissipation through Internet; sequence alignment and comparison methods; structure recognition and prediction algorithms; shotgun assembly procedures and algorithms; and scripting languages for linking together an automatic biological data processing pipeline. Focus will be on the analysis and actual implementation of those algorithms.

BCB 599. Creative Component
Cr. var.

Course for Graduate Students

BCB 690. Student Seminar in Bioinformatics and Computational Biology
Cr. 1, each time taken. S. Student research presentations.

BCB 691. Faculty Seminar in Bioinformatics and Computational Biology
(1-0) Cr. 1, each time taken. F. Faculty research series.

BCB 697. Graduate Research Rotation
Cr. var. each time taken. F.S.SS. Graduate research projects performed under the supervision of selected faculty members in the Bioinformatics and Computational Biology major.