Computational advances and the development of high throughput sequencing methods have led to a virtual explosion of genomics, proteomics, and metabolomics data, providing new approaches to problems in biosciences. The computer-aided analysis of these data with new tools from information science comprises the field of Genomics/Bioinformatics. The Genomics/Bioinformatics option examines the use of computational techniques to convert large amounts of information from DNA sequencing, DNA chips, and other high-throughput experimental methods into useful information that can be shared with other research scientists and medical professionals. The emphasis is on DNA and protein sequence alignment and analysis, and involves computational biology and biological statistics. Students will acquire skills preparing them for jobs or graduate programs in this new, rapidly growing field.
Students are required to take one or two courses in each of four areas:
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Biochemistry/Molecular Biology
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Genetics/Organismal Biology
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Computer Science
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Statistics/Modeling
In addition, students are required to do an internship in biocomputing, as a prerequisite to, or concurrent with starting, their research projects.
Mathematics
Substitute MTH 231. Elements of Discrete Mathematics (4)
and MTH 232. Elements of Discrete Mathematics (4)
for MTH 251. *Differential Calculus (4)
and MTH 252. Integral Calculus (4)
Required
BRR 410. Internship (Biocomputing) (3)
1. Biochemistry/Molecular Biology:
Choose one course from below:
BI 314. Cell and Molecular Biology (4)
or BB 331. *Introduction to Molecular Biology (3)
2. Genetics/Organismal Biology:
Choose one course from below:
ANS 378. Animal Genetics (4)
BOT 321. Plant Systematics (4)
CSS/PBG 430. Plant Genetics (3)
FS 444. Forest Genetics (4) [Terminated 200901]
MB 302. General Microbiology (3)
3. Computer Science:
CS 161, CS 162. Introduction to Computer Science I, II (4,4)
4. Statistics/Modeling:
Choose one course from below:
BEE 471. Biosystems Modeling Techniques (3) [Terminated 201200]
CSS/CROP 590. Experimental Design in Agriculture (4)
ST 352. Introduction to Statistical Methods (4)
Specialization and Breadth Courses
Choose from the list below, or other upper-division courses approved by research mentor, for a total of 29 option credits:
BB 481. Biophysics (3)
BB 494. Biochemistry Laboratory (3)
CS 261. Data Structures (4)
CS 325. Analysis of Algorithms (4)
CS 420. Graph Theory with Applications to Computer Science (3)
MB 310. Bacterial Molecular Genetics (3)
MB 311. ^Molecular Microbiology Laboratory: A Writing Intensive Course (3)
MB 554. Genome Organization, Structure and Maintenance (4) [Terminated 201201]
MB 668. Bioinformatics and Genomics (4)
ST 411, ST 412. Methods of Data Analysis (4,4)
ST 421, ST 422. Introduction to Mathematical Statistics (4,4)
ST 441. Probability, Computing, and Simulation in Statistics (4)
Total = 29
2004 Oregon State University