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, 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.

Associated BME Faculty

• BME faculty in genomics, bioinformatics, and systems biology

Focus Area Criteria

Each focus area consists of the following criteria:

• Required Courses: Complete four mandatory courses within your focus area.
• Engineering Topics: Select and complete two courses from the designated list of engineering topics relevant to your focus area.
• Electives: Choose five additional elective courses. These electives may be selected from:
  • The suggested electives list (see the curriculum map document above)
  • Courses required for a minor or certificate
  • Up to 3 semester hours of research credit
  • Other courses not listed, provided they receive approval from your academic advisor and the Biomedical Engineering (BME) department
  • Computational bioengineering students can use this guide for selecting courses with machine learning content

Approval for these electives is obtained through the submission of the Plan of Study form. Each student is encouraged to tailor their Plan of Study to include a cohesive set of courses that align with their personal career objectives. Faculty advisors are available to assist students in selecting the most appropriate courses for their Plan of Study. The focus area courses are in addition to the other BME degree requirements, which include engineering courses, math and science courses, general education courses, and seminars.

Example curriculum maps are provided for students interested in the following areas. Note that these are a suggested set and sequencing of elective courses; students can modify the courses and timing of the courses as desired based on their interests.