Bioinformatics is the application of computational and statistical methods to molecular biology. In the realm of biological and medical science, bioinformatics is a central discipline and is placing a new demand on the training of graduate students and other scientists in the biological and computer sciences. 

The educational objective of the graduate certificate program in bioinformatics is to provide added formal training for graduate students currently enrolled at UW–Madison to improve their fundamental skills in bioinformatics. The goal is to allow them to have enough basic knowledge to continue their own research and to collaborate with computer scientists specializing in bioinformatics methods.

The Department of Biostatistics and Medical Informatics is the administrative home of the bioinformatics certificate program.

You must be currently enrolled in a graduate program at UW–Madison.

To apply for the certificate program you must provide the following:

Please submit the listed materials to Beth Bierman, graduate coordinator,

For additional information about the certificate program, see Graduate Certificate in Bioinformatics   

Applications are accepted on a rolling basis.

The Graduate/Professional Certificate in Bioinformatics consists of four courses for a total of 12 credits. Three of the courses are required; one is an elective. Depending on their course and/or research load, students are given two years to complete the program.


MATH 222 Calculus and Analytic Geometry 24
COMP SCI 300 Programming II 13

Basic Course Requirements:

Choose ONE Statistics Course: 

B M I/​STAT  541 Introduction to Biostatistics3
or STAT/​F&W ECOL/​HORT  571 Statistical Methods for Bioscience I

Complete BOTH of these courses:

B M I/​COMP SCI  576
B M I/​COMP SCI  776
Introduction to Bioinformatics
and Advanced Bioinformatics

Choose ONE elective:

B M I/​STAT  542 Introduction to Clinical Trials I3
COMP SCI 540 Introduction to Artificial Intelligence3
COMP SCI 564 Database Management Systems: Design and Implementation4
COMP SCI 577 Introduction to Algorithms4
COMP SCI 731 Advanced Artificial Intelligence3
COMP SCI 760 Machine Learning3
COMP SCI 766 Computer Vision3
I SY E/​B M I/​L I S  617 Health Information Systems3
MATH 605 Stochastic Methods for Biology3
MATH/​B M I/​BIOCHEM/​BMOLCHEM  606 Mathematical Methods for Structural Biology3
MATH 608 Mathematical Methods for Continuum Modeling in Biology3