Bioinformatics and Computational Genetics, Biology and Genomics
Curriculum at Iowa

The field of Bioinformatics and Computational Biology (BCB) is characterized by an extremely diverse confluence of traditional academic disciplines. Biology and Computing are the most obvious allied disciplines, but a much larger array of areas contribute to the set of tools needed by individuals training for this new and expanding interdisciplinary field. Computer Engineering, Biomedical Engineering, Probability and Statistics, Computer Science, Biochemistry, Biology, Applied Mathematics, and Physics are some of the other allied fields.

BCB as an emerging discipline involves the creation of new methods for applying the capabilities of advanced mathematics and computation to problems of biological and biomedical interest. Examples of these problems include the understanding of the human genome, evolution of plants and animals, and the relationships between micro-organisms and higher-order forms of life. This list is by no means all-inclusive.

At the University of Iowa, the study of Bioinformatics is facilitated within a number of traditional areas of graduate and undergraduate study. There is a growing list of departments and degree programs that currently offer, or are making plans to offer, coherent adjunct curricula to students pursuing Bioinformatics. Here is a list of links to those programs:

Computational Genetics Subtrack of the Genetics Ph.D. Program
Ph.D. Program in Statistical Genetics
Carver Center for Comparative Genomics
Biotechnology Track in Biological Sciences
Health Informatics
Bioinformatics and Computational Biology Focus area in Biomedical Engineering
Computational Subtrack in Microbiology (coming soon)

Intro to Bioinformatics Bioinformatic Techniques

 

Additional Useful Coursework:
New courses are continually being developed to add to the list of courses above including courses in databases, algorithms, and proteomics. Depending on a student's area of interest for thesis research, the following courses are suggested as possibilities for further study and investigation:

Genetic Analysis of Biological Systems 127:150

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