Course variations

Course summary

This 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.

Program modules

The following are the modules: Required: BRR 410 Internship (Biocomputing) (3); Biochemistry/Molecular Biology: Choose one course from below: BI 314 Cell and Molecular Biology (4) or BB 331 Introduction to Molecular Biology (3); Students choosing the biochemistry/molecular biology emphasis choose 6 to 8 additional credits from below: BB 481 Biophysics (3); BB 494 Biochemistry Laboratory (3); MB 310 Bacterial Molecular Genetics (3); MB 311 Molecular Microbiology Laboratory: A Writing Intensive Course (3) or equivalent upper-division courses approved by research mentor Genetics/Organismal Biology: Choose one course from below: ANS 378 Animal Genetics (4); BOT 321 Plant Systematics (4); CSS 430 Plant Genetics (3); FS 444 Forest Genetics (4); MB 302 General Microbiology (3); Students choosing the genetics/organismal biology emphasis choose 6 to 8 additional credits from below: MB 310 Bacterial Molecular Genetics (3); MB 554 Genome Organization, Structure and Maintenance (4); MB 668 Bioinformatics and Genomics (4) or equivalent upper-division courses approved by research mentor Computer Science: CS 161, CS 162 Introduction to Computer Science I, II (4,4); Students choosing the computer science emphasis choose 6 to 8 additional credits from below: CS 261 Data Structures (4); CS 325 Analysis of Algorithms (4); CS 420 Graph Theory with Applications to Computer Science (3) or equivalent upper-division courses approved by research mentor to fulfill the computer science emphasis Statistics/Modeling: Choose one course from below: BEE 471 Biosystems Modeling Techniques (3); CSS 590 Experimental Design in Agriculture (4); ST 352 Introduction to Statistical Methods (4); Students choosing the statistics/modeling emphasis will choose 6 to 8 additional credits from below: 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) or equivalent upper-division courses approved by research mentor Specialization and Breadth Courses: 3 to 6 additional credits of upper-division courses approved by research mentor, for a total of 29 credits.

Entry requirement for international students

Applicants must have an excellent academic record (a minimum 3. 0 on a 4.0 scale or "B" grade average or equivalent) from an accredited or recognized institution to be admitted to Oregon State University. International students must have the following GPA scores: Paper score of 550; Internet score of 80 (Minimum score of 16 on each section) and IELTS score of 6.5.

Qualification

Bachelor degree

Awarding body

Oregon State University

Department name

College of Agricultural Sciences, Bioresource Research