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Bioinformatics Major

In order to major in bioinformatics, you must apply through the Center for Interdisciplinary Studies.

Learning Outcomes

Students who major in bioinformatics will learn to:

  • formulate hypotheses based on data presented in scientific publications
  • test hypotheses by mining databases to find supporting or contradictory evidence
  • design well controlled computer-based experiments that address tractable systems level questions
  • use databases to find information and locate details about specific proteins and genes
  • interpret complex data sets to address advanced biological questions
  • write computer code that can parse data and execute useful sequence analysis
  • construct software tools that require multiple programming languages and problem solving approaches
  • build web pages that clearly communicate complex information
  • construct mathematical models of biological processes
  • perform statistical analyses of datasets
  • manipulate cells and DNA in the wet lab
  • communicate summaries (written and oral) of complex data and the resulting conclusions
  • evaluate choices that produce ethical dilemmas and supporting conclusions with data


Malcolm Campbell, Professor of Biology & Genomics Director
Rachid El Bejjani, Assistant Professor of Biology
Laurie Heyer, Professor of Mathematics & Computer Science
Wendy Raymond, Professor of Biology & Vice President for Academic Affairs, Dean of Faculty
Nicole Snyder, Associate Professor of Chemistry


  •  Biology: one even number and one odd number from the following list: 111, 112, 113, 114
  •  MAT 112
  •  MAT 150 is recommended

Course Requirements

The major requires 12 courses, including the two CIS thesis courses. This major is intended for students who want to emphasize the math and computer science side of the Genomics program. 

Three computer science courses
  • CSC 209 Bioinformatics Programming
  • CSC 221 Data Structures
  • CSC 321 Analysis of Algorithms OR CSC 362 Data Visualization OR CSC 370 Artificial Intelligence OR CSC 371 Machine Learning
Four mathematics courses
  • MAT 140 Multivariable Calculus and Modeling
  • MAT 210 Mathematical Modeling
  • CSC/MAT 220 Discrete Structures
  • BIO 241 Biostatistics OR MAT 341 Math Statistics
Two biology courses
  • 309 Genomics, Proteomics and Systems Biology
  • 343 Laboratory Methods in Genomics
One Life Science Course
  • BIO 201 Genetics
  • BIO 202 Microbiology
  • BIO 208 Cell Biology
  • BIO 306 Developmental Biology
  • BIO 333 Cellular and Molecular Neuroscience
  • Biochemistry (BIO 303 or CHE 230) or
  • Immunology (BIO 307 or CHE 375)
Thesis (both courses required)
  • CIS 495 Thesis (fall)
  • CIS 496 Thesis (spring)