University of Connecticut University of UC Title Fallback Connecticut


Computational Foundations of Systems Biology  

BME 4985/BME 6086/CSE 4095/CSE 5095

The use of computers has become critical in many fields of science and engineering. In this course students will be introduced to computational systems biology which focuses on dynamic and intelligent features (e.g., adaptation and robustness) of biological systems such as gene networks. It will be emphasized the tools and methods of computational systems biology come from other computation-oriented disciplines which include computational physics, digital signal processing/control engineering, and digital logic. Students will also learn skills in programming using MATLAB, LabVIEW, JavaScript, and C# in the context of modeling, analyzing, estimating, and controlling real biological systems. Through a variety of assignments and projects, students will obtain a deeper understanding of physical and engineering principles applied to biological systems.

Computational Modeling/BioMEMS for Systems Biology  

BME 6086/ECE 6095 

Systems biology is a relatively new field, which studies complex interactions within biological systems. Computational modeling plays an important role in the study of systems biology as it can unravel complex dynamics often difficult to see intuitively. Considering the complex nature of biological systems, biological models should always be validated using relevant experiments, and BioMEMS (Biological or Biomedical MicroElectroMechanical Systems) provides an innovative platform for such experiments. BioMEMS is the science and technology of constructing devices or systems, using methods inspired from micro or nano-scale fabrication, that are used for processing, delivery, manipulation, analysis,or construction of biological and chemical entities. In this course, students will be introduced to BioMEMS with an emphasis on systems biology applications. Integrating BioMEMS with computational modeling for innovative systems biology research is interdisciplinary in nature and requires knowledge and skills for applying molecular biology, chemistry, physics, medicine, engineering, computer science, etc. Through a variety of projects, students will obtain a basic understanding of integrating BioMEMS and computational modeling for systems biology applications.