Students participating in the BD4ISU program are advised by program faculty on key courses to take as part of the program. Students in the program take roughly one course per term outside of their major as part of the program.  The student's completion of their major and foundational studies, of course, takes first priority.

Students take courses in Biology, Computer Science, and Mathematics as part of the program.  The following lists which courses should be taken, depending on the student's major.  For example, a Biology major takes BIO 101, all students in the program take BIO 487, and non-biology majors take BIO 112.

  • Biology

    • Non-biology majors - BIO 112 Human Aspects of Biology, BIO 102 & lab Principles of Biology II, BIO 481 Genome Science, BIO 491 Survey of Genetics (new course to be created)
    • Biology majors - BIO 101 & lab Principles of Biology I, BIO 102 & lab Principles of Biology II, CHEM 103 & lab Elementary Chemistry, CHEM 104 & lab Elementary Organic and Biochemistry, BIO 380 Genetics, BIO 492 Special Problems in Biology (research in bioinformatics)
    • All - BIO 487 Bioinformatics
    • Note - a key learning outcome is to have a firm grounding in the technology behind biomedical data and the strengths/limitations of the data
  • Computer Science
    • CS majors - CS 202 Computer Science II, CS 303 Discrete Structures, CS 457 Database Processing, CS 458 Algorithms, CS 475 Artificial Intelligence
    • All - CS 151 Intro to Programming, CS 201 Computer Science I, CS XYZ Programming for the Sciences (new course to be created)
    • Maybe - new visualization course
    • Note - a key learning outcome is to be very competent at manipulating data (cleaning, filtering, normalizing, selecting/combining), and managing a project in a way that is well documented and reproducible
  • Mathematics
    • Math majors - MATH 252 Programming in Mathematics, MATH 436 Numerical Analysis, MATH 441 Theory of Probability, MATH 442 Mathematical Statistics, 
    • All - MATH 131 Calculus I (and pre-requisites if not calculus-ready), MATH 132 Calculus II, MATH 241 Principles of Statistics, MATH 313 Elementary Linear Algebra, MATH 342 Applied Statistics (new course to be created)

Note - see also the Translational Data Analytics Institute at The Ohio State University for more on curriculum at OSU.