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U of M Minor Program in Bioinformatics

Bioinformatics is an interdisciplinary research area that applies computer and information science to solve biological problems. The graduate minor in bioinformatics includes core coursework in computer and biological sciences and opportunities to interact with others interested in bioinformatics. The curriculum encourages interdisciplinary interaction, communication, and synthesis. The minor is only available to students already enrolled in a major offered by the UMN Graduate School.

The core courses in bioinformatics are Computational Techniques for Genomics covering algorithms and data structures useful in the field and one from a selection of courses in applied genomics or sequence analysis. The third core course is Genetics or Molecular Evolution (for computer science majors) or Practice of Database Systems or Principles of Database Systems (for non-computer-science majors). Non-computer science majors may follow the computer-science branch with DGS approval.

The masters minor program has the three core courses (9 cr). The doctoral minor program has five courses: the core courses plus one of two courses in statistical genomics and one course not in the student's major field from a list of relevant electives or another course with DGS approval (15 cr minimum). All courses taken to fulfill minor requirements must be graded on the "A/F" scale.

Depending on a student's background, one or more designated prerequisite courses may be recommended prior to starting the minor program. Prerequisite courses may not be used to fulfill minor field requirements. Prerequisite courses may be graded on the "S/N" scale.

The following briefly describes each course; course prerequisites follow each course, except for electives. Longer course descriptions are available in the U of M Course Database. The exact timing of each course is available in the U of M Course Schedule. This description of the U of M graduate bioinformatics minor curriculum is also available in printer-friendly .pdf format.

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Recommended Prerequisites

For students deficient in computer science

  • CSci 4041.
    Algorithms and Data Structures 4cr - staff
    (prereq CSci 1902 and 2011 or instr consent)

For students deficient in biology, one of the following courses:

  • BioC 6021.
    Biochemistry 3cr - staff
    (prereq general biology, organic chemistry, instr consent)
  • BMEn 5501.
    Biology for Biomedical Engineering 3-4cr - staff
    (prereq Engineering upper div or grad student)

For doctoral students deficient in statistics, one of the following 4 cr courses:

  • PubH 6450.
    Biostatistics I - staff
    ([[Math 1111 or Math 1201], hlth sci grad student] or instr consent)
  • Stat 5021.
    Statistical Analysis - staff
    (College algebra or instr consent)

Core Courses

  • Fall - CSci 5481.
    Computational Techniques for Genomics - 3 cr - G. Karypis
    (CSci 4041 or instr consent)

AND one 3 cr course from the following:

  • Fall - PBio/PlPa 5301.
    Plant Genomics - N. Young
    ([Intro course in genetics, intro course in biochemistry] or instr consent)
  • Spring - Phcl 5111.
    Pharmacogenomics - C. Campbell
    (Grad student or instr consent)
  • Fall - BioC 5361.
    Microbial Genomics and Bioinformatics - L. Wackett and A. Kohdursky
    (College-level courses in [organic chemistry, biochemistry, microbiology])

And one 3 cr course from the following:

(for non-computer-science majors, one course from the following: they can follow cs-major branch with DGS approval)

  • CSci 4707.
    Practice of Database Systems - staff
    (CSci 4041 or instr consent)
  • CSci 5707.
    Principles of Database Systems - staff
    (CSci 4041 or instr consent)

(for computer-science majors, one 3 cr. course from the following)

  • Biol 4003.
    Genetics - staff
    (Biol/BioC 3021 or BioC 4331)
  • Spring - EEB 5221.
    Molecular and Genomic Evolution - G. May and A. Dean
    (Biol 4003, GCD 3022, or instr consent)

Total: 9 credits

For Doctoral students (the core plus the following)

One course of the following:

  • Fall - AnSc/CMB 5200.
    Statistical Genetics and Genomics
    4 cr - Y. Da, L. Alexander, S. Fahrenkrug
    ([Stat 3021 or equiv], [GCD 3022 or Biol 4004 or equiv])
  • Spring - PubH 7445.
    Statistics for Human Genetics and Molecular Biology
    3 cr - C. Reilly
    ([PubH 6450 or equiv] or instr consent; bkgd in mol. biol. desired)

AND one 3 or 4 cr elective not in a student's major field. Choose from the following or many others with DGS approval. Course prerequisites, not listed below, must be met.

  • BioC 4950. Computer Simulation and Data Analysis in Biochemistry. V. Bloomfield
  • ChEn 8754. Systems Analysis of Biological Processes. W-S. Hu
  • Chem 5021/8021. Computational Chemistry. J. Gao
  • CSci 5521. Pattern Recognition. D. Boley
  • CSci 5523. Introduction to Data Mining. V. Kumar
  • CSci 5980. Functional Genomics, Systems Biology and Bioinformatics. R. Kuang & C. Myers
  • CSci 8725. Databases for Bioinformatics. J. Carlis
  • EEB 5033. Population and Quantitative Genetics. R. Shaw, J. Curtsinger
  • EEB/Ent 5371. Principles of Systematics. R. Zink, S. Weller
  • EEB 5963. Modeling Nature and the Nature of Modeling. C. Neuhauser
  • Math 8540. Topics in Mathematical Biology. H. Othmer
  • NSc 5201. Computational Neuroscience I: Membranes and Channels. J. Fohlmeister
  • NSc 5202. Theoretical Neuroscience: Systems and information processing. A.D. Redish
  • Phys 5081. Introduction to Biopolymer Physics. A. Grosberg
  • PubH 6381. Genetics in Public Health (2 cr) and
  • PubH 6385. Computational Methods in Genetic Epidemiology (2 cr). M. Miller
  • PubH 7475. Statistical Learning and Data Mining. W. Pan

Total: 15 - 17 credits