Overview

Systems and synthetic Biomedical Engineering are complementary emergent fields that combine experimental, computational and theoretical methods to solve challenging biomedical problems. Systems Biomedical Engineering is based on a holistic approach of integrating large amounts of molecular information to elucidate the relationship between genotype and phenotype. This multi-scale understanding of biological systems will help answer important questions about physiological systems, human disease, and therapeutic strategies. Synthetic Biomedical Engineering is the design and construction of biological systems from molecular biological components for useful purposes. Such systems have applications in a wide range of complex biomedical problems.

Among the greatest challenges in these fields are how to obtain, manipulate, and interpret massive datasets. Research in this area also requires a multi-scale understanding of the system of interest, from molecules to cells to organisms to ecosystems. Computational systems and synthetic Biomedical Engineering draw from a wide range of specialties including mathematical modeling, scientific computing, signal processing, molecular biology, and high-throughput technologies to provide a unique approach to solving biomedical problems.

This track draws from the rich set of resources currently available at the University of Utah to provide students with valuable interdisciplinary academic and research experiences. Students will receive training in desirable skills, including large-scale data analysis and genomic technologies, making them well-suited for careers in academia, industry, and government.

Because computational systems and synthetic Biomedical Engineering are inherently interdisciplinary, the program supplements a strong Biomedical Engineering core with courses from a variety of departments. Below are summaries of the proposed course and research requirements for the track.

Masters Students

M.S. and M.E. students in the Computational Systems and Synthetic Biomedical Engineering track must successfully complete the core course requirements outlined below, as well as the total course credit hour requirement of the M.S. or M.E. degree programs. At least nine (9) credit hours from the following core courses:

  • BME 6670 – Genomic Signal Processing
  • BME 6900 – Principles of Synthetic Biology
  • BME 6760 – Modeling and Analysis of Biological Networks
  • PH TX 7777 and 7778 – Applied Genomics I and II

At least six (6) additional credit hours from graduate level courses related to the specific computational or mathematical research area of interest, for example:

  • CS 6210 – Scientific Computing I
  • CS 6957 – Probabilistic Modeling
  • MATH 7875 – Applied Mathematics Seminar

 

Ph.D. Students

Ph.D. Qualifying Exam

Ph.D. students in the Computational Systems and Synthetic Biomedical Engineering track are expected to have general knowledge in computational and numerical methods as well as in systems and synthetic biomedical engineering, with a specific focus in one biomedical engineering application. A student who, for example, applies computational methods to problems in cancer genomics, should have knowledge in both areas. The material for the exam will be based primarily on topics covered in the core courses. However, there will be a strong emphasis on the integration of computational approaches and the target area of application, material not likely to be covered explicitly in any course or textbook.

Program of Study

The course selection that will be appropriate for each student in the Computational Systems and Synthetic Biomedical Engineering track will vary and depend highly on the specific research project in which the student participates. It will be especially important to choose courses that provide both the scientific background and the technical skills required to carry out this research. The Program of Study is a list created by the student and the supervisory committee of all courses to be completed by the student as part of the requirements for the Ph.D. The Program of Study requires formal approval by the student’s advisor, Dissertation Supervisory Committee, and Director of Graduate Studies.

Additional Courses

Below is a selection of courses available at the University of Utah that may be appropriate for the Computational Systems and Synthetic Biomedical Engineering track.


Biomedical Engineering


Biology

  • BIOL 5110 – Molecular Biology and Genetic Engineering
  • BIOL 5140 – Genome Biology
  • BIOL 6420 – Genetics and Genome Organization
  • BIOL 6500 – Advanced Statistical Modeling for Biologists


Biological Chemistry

  • BLCHM 6400 – Genetic Engineering


Biomedical Informatics

  • BMI 6030 – Foundations of Bioinformatics
  • BMI 6420 – Advanced Biomedical Computing
  • BMI 6530 – Bioinformatics Data Integration and Analysis


Computer Science

  • CS 6140 – Data Mining
  • CS 6150 – Advanced Algorithms
  • CS 6220 – Scientific Computing II
  • CS 6350 – Machine Learning
  • CS 6530 – Database Systems
  • CS 7120 – Information-Based Complexity


Electrical and Computer Engineering

  • ECE 6520 – Information Theory
  • ECE 6530 – Digital Signal Processing
  • ECE 6540 – Estimation Theory
  • ECE 6550 – Adaptive Filters
  • ECE 6570 – Adaptive Control


Family and Preventive Medicine

  • FPMD 6107 – Survival Analysis
  • FPMD 7120 – Linear and Logistic Regression Models


Human Genetics

  • HGEN 5265 – Eukaryotic Genetics
  • HGEN 6500 – Human Genetics
  • HGEN 6503 – Cancer Genetics


Mathematics

  • MATH 6770 and 6780 – Mathematical Biology I and II
  • MATH 6810 and 6815 – Stochastic Processes and Simulation I and II
  • MATH 6845 – Ordinary Differential Equations and Dynamical Systems
  • MATH 6855 – Survey of Numerical Methods
  • MATH 6860 and 6865 – Introduction to Numerical Analysis I and II


Molecular Biology

  • MBIOL 6420 – Genetics and Genome
  • MBIOL 6440 – Gene Expression


Medicine Clinical Research Center

  • MDCRC 6150 – Foundations in Personalized Health Care
  • MDCRC 6420 – Genetics of Complex Diseases

More Information on the Ph.D. Program

Questions?

Please contact Dr. Orly Alter or Dr. Tamara Bidone.