Computational Bioengineering Focus Area

(Formerly called Bioinformatics Focus Area)

What is Computational Bioengineering? 

Computational Bioengineering combines principles of engineering, biology, and medicine to improve human health using computational approaches. These approaches are applied from atomic resolution up to an entire organ or system of organs, including the following examples that draw from on ongoing research in the department: 

  • at atomic resolution, cellular building blocks (e.g., proteins, nucleic acids, lipids, sugars) are simulated to understand their function in healthy cells, and how genetic mutations cause disease, and that can ultimately lead to the design of new therapeutics.
  • at the resolution of cells and tissues, computational bioengineers simulate response to injury to understand and facilitate wound healing and design implants.
  • at the resolution of organs and organ systems, imaging methods (e.g., CT, MRI) are used to understand the biomechanics and model organs (e.g., lung, heart, brain, etc.).
  • across multiple resolutions and time scales, “multi-omics” analysis of large data sets generated from nucleic acid sequencing (DNA and RNA), metabolomics, and etc., are used to help understand the genetic basis of disease mechanisms and design precision treatments.

Given the scope and complexity involved in probing biology across resolutions, this area builds on fundamental disciplines (e.g., mathematics, physics, chemistry, statistics, computer science, engineering) to model, analyze, and understand biological data. This understanding forms the basis for translational biomedical applications that improve human health. Students in Computational Bioengineering will pursue careers in a broad range of fields including:   biomedical software engineering, biomolecular engineering, biotechnology, cell-based therapy development, gene therapies, genetic engineering, computational drug design and/or modeling, medical technologies, biological devices and/or embedded systems, biological sensors, systems and network biology, bioinformatics, computational biology, machine learning, or health informatics.


Computational Bioengineering Curriculum Map 3/23/22 | Sample Four-Year Plan 5/20/22

computational bioengineering course map

computational bioengineering course list

 

 

Note: At least two electives (6 s.h.) must be from the list of Engineering Topics. An additional 21 s.h. of electives are also required (suggested electives list, minor, or certificate courses).
Please check MyUI for the most up to date course offerings and pre/corequisites.
Terminology from “Track” to “Focus Area” was updated in the website text on 03/16/21

*Computational Bioengineering students can take ENGR:2130 as an Engineering Topic if they have taken ENGR:2995 as an Engineering Core (and vice versa)

Please consult this guide when selecting electives that have machine learning content.

Check the Computational Bioengineering Curriculum Map and Sample Four-Year Plan links above for more details.

Computational Bioengineering Academic Advisors


Terry Braun

Thomas Casavant

Michael Schnieders

 

Link to previous Bioinformatics Focus Area Curriculum Map