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BS in Bioinformatics
(67 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; Summer
      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:
      BIO 450 : Conservation Biology. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 450 : Conservation Biology. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: BIO 220A & BIO 350; or BIO 220B & BIO 350
      DESCRIPTION: Scientific principles of conservation: applying population genetics, and phylogenetic and ecological theory to preservation of biological diversity; developing sustainable ecological systems compatible with human resource use.

      Course Outcomes


      BIO 463 : Genetics of Human Disease. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 463 : Genetics of Human Disease. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: PWS 340
      DESCRIPTION: Examining the application of genetics to understanding and treatment of human disease. Functional consequences of mutations; use of model organisms; linkage and association analysis of complex traits; pharmacogenetics; ethical considerations.

      Course Outcomes


      BIO 468 : (Bio-MMBio-PWS) Genomics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 468 : (Bio-MMBio-PWS) Genomics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: MMBIO 240 & PWS 340
      DESCRIPTION: Current analysis of genes and genomes; computational and statistical approaches for analyzing genomic data, including genome sequencing and annotation, gene expression and the transcriptome, proteomics and functional genomics, and genetic variation and SNPs.

      Course Outcomes


      BIO 555 : Evolutionary and Ecological Modeling. (2:2:0)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 555 : Evolutionary and Ecological Modeling. (2:2:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter Even Yrs.
      PREREQUISITE: Senior status in bioinformatics program or graduate status; Stat 511, 512, or equivalent; instructor's consent.
      DESCRIPTION: Using models in ecology. Practical experience in analytical, simulation, and agent-based models.

      Course Outcomes


      BIO 560 : Population Genetics. (4:4:0)(Credit Hours:Lecture Hours:Lab Hours)
      BIO 560 : Population Genetics. (4:4:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall Contact Department; Winter Contact Department
      PREREQUISITE: Bio 420 or equivalent.
      DESCRIPTION: Basic principles of population genetics applied to natural populations; drift, selection, and nonrandom mating; inferring population subdivision, migration, and gene flow.

      Course Outcomes


      C S 312 : Algorithm Design and Analysis. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 312 : Algorithm Design and Analysis. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: C S 240 & C S 252
      DESCRIPTION: A study of the design and analysis of algorithms as solutions to problems, including dynamic programming, linear programming, greedy algorithms, divide-and-conquer algorithms, graph algorithms, and intelligent search algorithms.

      Course Outcomes


      C S 340 : Software Design and Testing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 340 : Software Design and Testing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: C S 240
      DESCRIPTION: Principles of software design, design patterns, design representation, refactoring. Principles of software quality assurance and testing. Development and testing tools.

      Course Outcomes


      C S 450 : Introduction to Digital Signal and Image Processing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 450 : Introduction to Digital Signal and Image Processing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: C S 312 & C S 355 & MATH 313
      RECOMMENDED: Stat 121.
      DESCRIPTION: One- and two-dimensional signal-processing fundamentals, including sampling, noise, transforms, filtering, enhancement, and compression. Hands-on experimentation with speech, music, still images, and full-motion video.

      Course Outcomes


      C S 452 : Database Modeling Concepts. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 452 : Database Modeling Concepts. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: C S 240
      DESCRIPTION: Database models: relational, deductive, object-oriented. Integrity constraints, query languages, database design.

      Course Outcomes


      C S 470 : Introduction to Artificial Intelligence. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 470 : Introduction to Artificial Intelligence. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Spring
      PREREQUISITE: C S 312 & MATH 313 & STAT 121; or instructor's consent.
      DESCRIPTION: Introduction to core areas of artifical intelligence; intelligent agents, problem solving and search, knowledge-based systems and inference, planning, uncertainty, learning, and perception.

      Course Outcomes


      C S 478 : Tools for Machine Learning and Data Mining. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 478 : Tools for Machine Learning and Data Mining. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter; Spring
      PREREQUISITE: C S 312 & MATH 313 & STAT 121
      DESCRIPTION: Machine learning and data mining models and other mechanisms allowing computers to learn and find knowledge from data.

      Course Outcomes


      C S 484 : Parallel Processing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      C S 484 : Parallel Processing. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: C S 360
      DESCRIPTION: Theoretical and practical study of parallel processing including multi-core, fine-grained, and clustered architectures, parallel programming languages, and parallel algorithms.

      Course Outcomes


      CHEM 351 : Organic Chemistry. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 351 : Organic Chemistry. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: CHEM 105; or CHEM 111
      DESCRIPTION: Chemical bonds and molecular structure, conformation and configuration, functional classes, reactions and mechanisms, syntheses.
      NOTE: Primarily for majors in chemical engineering and the biological sciences.

      Course Outcomes


      CHEM 352 : Organic Chemistry. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 352 : Organic Chemistry. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring; Summer
      PREREQUISITE: CHEM 351; or CHEM 351M
      DESCRIPTION: Continuation of Chem 351.

      Course Outcomes


      CHEM 353 : Organic Chemistry Laboratory--Nonmajors. (1-2:0:6)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 353 : Organic Chemistry Laboratory--Nonmajors. (1-2:0:6)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring; Summer
      PREREQUISITE: Chem 352 or Chem 352M or concurrent enrollment (preferred).
      DESCRIPTION: Physical and chemical properties, isolation and purification, characterization, syntheses.
      NOTE: For predentistry, premedicine, and other majors who do not intend to take Chem 455.

      Course Outcomes


      CHEM 481 : Biochemistry. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: CHEM 352M & PDBIO 120; or CHEM 352 & PDBIO 120
      DESCRIPTION: First-semester biochemistry. Molecular components of cells, chemical structure and function, enzymes, metabolic transformations, photosynthesis.
      NOTE: For chemistry majors and students in biological sciences who contemplate pursuing advanced degrees, including medicine. (For prerequisite, Bio 130 may be used in place of PDBio 120.)

      Course Outcomes


      CHEM 482 : Mechanisms of Molecular Biology. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 482 : Mechanisms of Molecular Biology. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: CHEM 481M; or CHEM 481
      DESCRIPTION: Second-semester biochemistry. Nucleic acid biochemistry and molecular biology: nucleotide metabolism, chromosome and chromatin structure, DNA structure and replication, RNA transcription and gene expression, protein synthesis and regulation, eukaryotic gene systems, signal transduction.

      Course Outcomes


      CHEM 489 : Structural Biochemistry. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 489 : Structural Biochemistry. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: CHEM 468
      DESCRIPTION: Molecular structures of proteins, RNA and DNA as determinants of biological function. Topics include thermodynamics of folding and binding, structural determination, spectroscopy, modeling, protein recognition.

      Course Outcomes


      CHEM 584 : Biochemistry Laboratory/Proteins. (3:1:6)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 584 : Biochemistry Laboratory/Proteins. (3:1:6)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: CHEM 481M; or CHEM 481
      DESCRIPTION: Introduction to current biochemical research procedures including spectrophotometry, chromatography, electrophoresis, and immunological techniques. Protein over-expression; isolation and characterization methods. Enzyme kinetics and protein-ligand interactions. Introduction to bioinformatics.
      NOTE: May be taken before or after Chem 586.

      Course Outcomes


      CHEM 586 : Biochemistry Laboratory/Nucleic Acids. (3:1:6)(Credit Hours:Lecture Hours:Lab Hours)
      CHEM 586 : Biochemistry Laboratory/Nucleic Acids. (3:1:6)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: CHEM 482
      DESCRIPTION: Laboratory course covering major techniques involved in isolation, amplification, and cloning of recombinant DNA as well as isolation, synthesis, translation, and identification of RNA.
      NOTE: May be taken before or after Chem 584.

      Course Outcomes


      MATH 313 : Elementary Linear Algebra. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      MATH 313 : Elementary Linear Algebra. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      OFFERED: Honors also.
      WHEN TAUGHT:Fall; Winter; Spring; Summer
      PREREQUISITE: Math 112.
      RECOMMENDED: Math 290.
      DESCRIPTION: Linear systems, matrices, vectors and vector spaces, linear transformations, determinants, inner product spaces, eigenvalues, and eigenvectors.

      Course Outcomes


      MATH 334 : Ordinary Differential Equations. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      MATH 334 : Ordinary Differential Equations. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring; Summer
      PREREQUISITE: Math 113 and Math 313.
      DESCRIPTION: Methods and theory of ordinary differential equations.

      Course Outcomes


      MATH 410 : Introduction to Numerical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      MATH 410 : Introduction to Numerical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: MATH 314; C S 142 or equivalent.
      DESCRIPTION: Root finding, interpolation, curve fitting, numerical differentiation and integration, multiple integrals, direct solvers for linear systems, least squares, rational approximations, Fourier and other orthogonal methods.

      Course Outcomes


      MATH 411 : Numerical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      MATH 411 : Numerical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: MATH 334
      DESCRIPTION: Iterative solvers for linear systems, eigenvalue, eigenvector approximations, numerical solutions to nonlinear systems, numerical techniques for initial and boundary value problems, elementary solvers for PDEs.

      Course Outcomes


      MATH 431 : (Math - EC En 370) Probability Theory. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      MATH 431 : (Math - EC En 370) Probability Theory. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Contact Department.
      PREREQUISITE: MATH 313
      DESCRIPTION: Axiomatic probability theory, conditional probability, discrete / continuous random variables, expectation, conditional expectation, moments, functions of random variables, multivariate distributions, laws of large numbers, central limit theorem.

      Course Outcomes


      MATH 450 : Combinatorics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: MATH 371
      DESCRIPTION: Permutations, combinations, recurrence relations, applications.

      Course Outcomes


      MMBIO 360 : Microbial Genetics. (4:3:3)(Credit Hours:Lecture Hours:Lab Hours)
      MMBIO 360 : Microbial Genetics. (4:3:3)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: MMBIO 240
      DESCRIPTION: How DNA governs complex bacterial functions. Classical and modern approaches to gene discovery, including genetic screens, gene mapping, targeted genetic manipulations, and analyzing gene activity.

      Course Outcomes


      MMBIO 465 : Virology. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: MMBio 261 or equivalent.
      DESCRIPTION: Basic principles of virology, emphasizing selected molecular aspects of virus life cycles and disease processes.

      Course Outcomes


      PDBIO 360 : Cell Biology. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: MMBIO 240; or CHEM 481M; or CHEM 481
      DESCRIPTION: Fundamentals of cell structure and function with reference to analytical methods used by cell biologists. Practice in designing, executing, and interpreting relative experiments.

      Course Outcomes


      PDBIO 362 : Advanced Physiology. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      PDBIO 362 : Advanced Physiology. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter; Spring
      PREREQUISITE: MMBIO 240 & PHSCS 106; or MMBIO 240 & PHSCS 220
      DESCRIPTION: Integrated approach to organ system and cellular physiology. Problem solving/calculations.
      NOTE: Requires background in chemistry and molecular biology. Students without this background should take PDBio 305.

      Course Outcomes


      PDBIO 482 : Developmental Biology. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      PDBIO 482 : Developmental Biology. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall; Winter
      PREREQUISITE: MMBIO 240 & PDBIO 360
      RECOMMENDED: PDBio 325.
      DESCRIPTION: Invertebrate and vertebrate developmental biology. Embryonic gastrulation, neurulation, pattering, etc. Modern approaches and research strategies. Emphasizes gene function, cell signaling, signal transduction during embryogenesis.

      Course Outcomes


      PDBIO 582 : Developmental Genetics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      PDBIO 582 : Developmental Genetics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: PDBio 482 or equivalent.
      DESCRIPTION: Gene function and regulation during cell specification and differentiation, pattern formation, and organogenesis in developing embryo.

      Course Outcomes


      STAT 424 : Statistical Computing. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
      STAT 424 : Statistical Computing. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: STAT 223 & STAT 224 & STAT 330
      DESCRIPTION: Create and interact with relational databases comprised of large real world data; integrate previous course work into a single research project from formulation to final report; solve statistical problems using a combination of SAS, R, and SQL skills.

      Course Outcomes


      STAT 431 : Experimental Design. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      STAT 431 : Experimental Design. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Fall
      PREREQUISITE: STAT 330
      DESCRIPTION: Basic designs, power and sample size, Latin squares, incomplete blocks, change-over designs, factorials, fractional factorials, confounding, split-plots, response surface designs.

      Course Outcomes


      STAT 435 : Nonparametric Statistical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      STAT 435 : Nonparametric Statistical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
      WHEN TAUGHT:Winter
      PREREQUISITE: STAT 330; or STAT 511
      DESCRIPTION: Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, curve fitting.

      Course Outcomes


*Hours include courses that may fulfill university core requirements.



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