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Undergraduate Catalog

2013 - 2014

BS in Bioinformatics
(66 hours*)


Program Objectives

Bioinformatics is an interdisciplinary program offering substantial training in both the biological sciences and the physical and mathematical sciences, with an emphasis on computer programming coupled with genetics and molecular biology. Students are expected to acquire programming, databasing, and operating system skills coupled with a foundation in mathematics and statistics. In addition, students will receive broad training in the basic concepts of biology and chemistry. Students attracted to this program have dual interests in math/computer science and biology, and find it an exceptional option for their broad interests.


Program Requirements    |    View MAP   |    View Program Outcomes

  1. Complete the following:
  2. Complete one course from the following:
      BIO 365 : Computational Biology. (3:2:1)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 365 : Computational Biology. (3:2:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: C S 240
      DESCRIPTION: Computational analysis of DNA data; introduction to bioinformatics databasing using Perl and SQL; configuration of UNIX workstations for bioinformatics analyses.

      Course Outcomes


      C S 418 : Bioinformatics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter Contact Department; Spring Contact Department; Summer Contact Department
      PREREQUISITE: C S 312
      DESCRIPTION: Computational methods for analyzing biological systems. Dynamic programming, Markov models, Neural Networks, and Bayesian analysis are used to predict secondary structure, tertiary structure, and active sites for drug docking given molecular DNA sequence data.

      Course Outcomes


  3. Complete the following:
  4. Complete the following:
      STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Spring
      PREREQUISITE: MATH 112
      RECOMMENDED: Concurrent enrollment in MATH 113.
      DESCRIPTION: The scientific method; conditional probability; Bayes' Theorem; conjugate distributions: Beta-binomial, Poisson-gamma, normal-normal; Gibbs sampling.

      Course Outcomes


      STAT 201 : Statistics for Engineers and Scientists. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      STAT 201 : Statistics for Engineers and Scientists. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: MATH 112; or MATH 119
      DESCRIPTION: The scientific method; probability, random variables, common discrete and continuous random variables, central limit theorem; confidence intervals and hypothesis testing; completely randomized experiments; factorial experiments.

      Course Outcomes


  5. Complete six credit hours from the following upper-division electives in computer science, chemistry, mathematics, statistics, or biology:

*Hours include courses that may fulfill university core requirements.



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