Graduate

Genomics and Systems Biology Focus Area Curriculum Requirements

 

 

 

 

 

 

 

 

 

 

 

Genomics and Systems Biology is a discipline rooted in biomedical engineering that devotes advanced mathematical and modeling approaches to understand how the multiple scales that make up the human body maintain health and contribute to disease. Understanding life begins at the smallest of scales requiring a detailed understanding of how molecules assemble into the molecular machines that create cells that in turn constitute the tissues and organs that make up the human body. Understanding these multi-scale interactions is a staggering challenge that requires new approaches that combine network analysis theory with new ways of visualizing and manipulating biological networks across multiple spatial and temporal scales. Additional information, including our department’s Systems Biology faculty, is provided here.

Genomics and Systems Biology focus area students are expected to complete at least two of the following courses:
  • Systems Bioengineering I (EN.580.721)
  • Systems Bioengineering II (EN.580.722)
  • Models of the Neuron (EN.580.639)
  • Foundations of Computational Biology and Bioinformatics II (EN.580.688)
  • Computational Stem Cell Biology (EN.580.647)
  • Systems Pharmacology and Personalized Medicine (EN.580.640)
  • Computational Molecular Medicine (EN.553.650)
  • Cell Engineering (EN.580.641)
Genomics and Systems Biology focus area students will complete additional electives selected from the following list (choose at least three of these courses):
  • Tissue Engineering (EN.580.642)
  • Structure and Function of the Auditory and Vestibular Systems (EN.580.625)
  • Computational Genomics: Sequences (EN.601.647)
  • Computational Genomics: Data Analysis (EN.601.648)
  • Machine Learning (EN.601.675)
  • Machine Learning: Data to Models (EN.601.676)
  • Machine Learning: Deep Learning (EN.601.682)
  • Principles of Complex Networked Systems (EN.520.622)
  • Mathematical Foundations of BME I (EN.580.704)
  • Networked Dynamical Systems (EN.520.629)
  • Introduction to Linear Systems Theory (EN.520.601)
  • Metabolic Systems Biotechnology (EN.540.602)
  • Physical Epigenetics (EN.580.446)
  • Computational Protein Structure Prediction and Design (EN.540.614)
  • Practical Ethics for Future Leaders (EN.580.496)
Students will select additional graduate level science, technology, engineering, or math courses with the consent of their advisor to complete the total of 30 credits required for graduation.