Fall, 2016

Course Directors 

Jim Faeder (University of Pittsburgh) - faeder@pitt.edu - Office hours : after class or by appointment
Robin Lee (University of Pittsburgh) - robinlee@pitt.edu - Office hours: after class or by appointment
Andreas Pfenning (Carnegie Mellon University) - apfenning@cmu.edu - Office hours: TBD

Teaching Assistants

Kelvin Liu - 
Marcus Thomas - 
John Zhang -  

Course Description


This course will introduce students to the theory and practice of modeling biological systems from the molecular to the population level with an emphasis on intracellular processes. Topics covered include kinetic and equilibrium descriptions of biological processes, systematic approaches to model building and parameter estimation, analysis of biochemical circuits modeled as differential equations, modeling the effects of noise using stochastic methods, modeling spatial effects, and modeling at higher levels of abstraction or scale using logical or agent-based approaches. A range of biological models and applications will be considered including gene regulatory networks, cell signaling, cell cycle regulation, and pharmacokinetics and pharmacodynamics (PK/PD). Weekly lab sessions will provide students hands-on experience with methods and models presented in class. Course requirements include regular class participation, weekly homework assignments, a take-home exam, and a final project.


The course is designed for graduate and upper-level undergraduate students with a wide variety of backgrounds.  The course is intended to be self-contained but students may need to do some additional work to gain fluency in core concepts.  Students should have a basic knowledge of calculus, differential equations, and chemistry as well as some previous exposure to molecular biology and biochemistry.  Experience with programming and numerical computation is useful but not mandatory.  Laboratory exercises will use Matlab as the primary modeling and computational tool augmented by additional software as needed.

Course Requirements

  • Homework (30%) 
    • Weekly graded assignments based on class lectures and readings.
    • Lateness policy: 25% credit deducted per day for late assignments. Each student will receive 3 days of grace period credit to be distributed over assignments throughout the semester.  Further extensions will be granted only under extreme circumstances.  All assignments must be completed to pass the course.
    • Cheating policy: All work must be your own.  Unauthorized collaboration or plagiarism will result in a failing grade and will be reported to your academic advisor and dean.
  • Take-Home Exam (30%) 
    • One week for a problem set covering course topics. 
  • Project (40%) 
    • Model and analyze a biological network; or 
    • Design and implement a simulation or analysis tool for biological modeling.
    • A project proposal will be due mid-semester. See Proposals for more information.
    • The project will be graded by peer-review panels in the final week of the course and participation in this review process will count for 25% of the project grade.
    • Cheating policy: All work must be your own and novel.  Unauthorized collaboration, falsified data, or plagiarism will result in a failing grade and will be reported to your academic advisor and dean.
    • Double dipping policy:  You may not re-use data, reports, manuscripts, or publications from your research or from other courses. However, you  may extend your previous work, as long as you inform the instructors that you are doing so. Please contact the instructors if you have any questions regarding this policy.

Meeting Times

First day of class: Tuesday, September 1, 2015
Lectures: Tu,Th 1:30-2:50 pm, SCG 103*
Lab: Fr 1:30-3:30pm, SCG 110*

*Note: These rooms are in the Pittsburgh Supercomputing Center, 300 S. Craig Street. (directions)

Please see Course Calendar for additional details.

Required Text


Course Outline (tentative)

  1. Introduction
    1. Systems Biology (Faeder) [1 lecture]
    2. Introduction to Mathematical Modeling (Langmead) [1 lecture]
  2. Modeling Formalisms (Langmead) [2 lectures]
  3. Analysis of ODEs (Faeder) [2 lectures]
  4. Parameter Estimation (Langmead) [3 lectures]
  5. Biochemical Kinetics (Faeder) [3 lectures]
  6. Modeling Genetic Circuits (Faeder) [2 lectures]
  7. Modeling Stochasticity (Faeder) [2 lectures]
  8. Modeling Cell Signaling (Faeder) [1 lecture]
  9. Modeling the Cell Cycle (Faeder) [1 lecture]
  10. Spatial Modeling with PDEs (Langmead) [1 lecture]
  11. Spatial Stochastic Modeling (Faeder) [1 lecture]
  12. Population Models & Evolutionary Dynamics (Langmead) [2 lectures]
  13. Markov Models (Langmead) [2 lectures]
  14. PK/PD Modeling (Langmead) [1 lecture]
  15. Project Presentations (students) [2 lectures]

Recommended Texts

The following books may be useful as supplements to the main text and lectures.
  • Uri Alon, An Introduction to Systems Biology: Design Principles of Biological Networks, Chapman and Hall/CRC, ISBN-13: 978-1584886426.
  • Chris Myers, Engineering Genetic Circuits, Chapman and Hall/CRC, ISBN-13: 978-1420083248.
  • E. Klipp, R. Herwig, A. Kowald, C. Wierling, and H. Lehrach, Systems Biology in Practice: Concepts, Implementation, and Application, Wiley-VCH, ISBN-13: 978-3527310784. (Note: an updated version called Systems Biology: A Textbook is also now available.)
  • D. Kaplan and L. Glass, Understanding Nonlinear Dynamics. Springer. 1995. ISBN-13: 978-0387944401.
  • Eberhard Voit, A First Course in Systems Biology, Garland Science. 2012. ISBN-13: 9780815344674
  • Sarah Otto and Troy Day, A Biologist's Guide to Mathematical Modeling in Ecology and Evolution Princeton University Press,  ISBN-13: 978-0691123448
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