Research Publications Resume Teaching Miscellaneous

Life's Complexity Pyramid
(Z. N. Oltvai and A.-L. Barabási, Science 298, 763 (2002))

Systems Biology--Metabolic Engineering (BioE 474), Spring semester

Course Description: This Systems Biology course will cover a) the process of reconstructing complex biochemical reaction networks in cells and mathematically simulating their behaviors; b) reconstructing metabolic, gene regulatory and signaling networks; c) bottom-up and top-down approaches; d) principles underlying high-throughput experimental technologies and examples on how this data is used for network reconstruction, consistency checking, and validation; e) classical kinetic theory; and f) constraints-based models. Methods that are scalable and integrate multiple cellular processes will be emphasized. Existing genome-scale models will be described and computations performed. Emphasis will be on studying the genotype-phenotype relationship in an in silico model driven fashion, and comparisons with phenotypic data will be emphasized.

Course Goals: The course will introduce the student to the emerging field of systems biology - the intersection between high-throughput biological data integration and computational modeling. This course will focus primarily on the reconstruction and analysis of biochemical reaction networks (metabolic, regulatory, and signaling) in cells as a basis for systems biology research and synthetic biology designs. By the end of this course, students will be able to:

  • Reconstruct biochemical networks of various types from biological data
  • Analyze the properties of these networks using a variety of techniques, including linear programming, convex analysis, and single value decomposition (if time permits)
  • Reconstruct metabolic and gene regulatory networks
  • Design mathematical models for a variety of metabolic processes and interpret the meaning of the network model simulations for the biological systems they represent