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: after class or by appointment

For quickest response, please send email to csm2016-instructors@googlegroups.com

Teaching Assistants

She Zhang -  shz66@pitt.edu - Office hours: cubicles on 3rd floor of BST3 (Biomedical Science Tower)

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. A range of biological models and applications will be considered including gene regulatory networks cell signaling, neuroscience, population dynamics, and evolution. Weekly recitations will introduce computational skills and provide students hands-on experience with methods and models presented in class. Course requirements include weekly homework assignments, a final project, and a take-home exam.


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. 
  • 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.
  • Take-Home Exam (30%) 
    • One week for a problem set covering course topics. 

Meeting Times

First day of class: Tuesday, August 30, 2016
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)

Required Text

Physical Biology of the Cell, 2nd edition (PBOC). Reading and homework assignments will be drawn from this book. It has not been pre-ordered at campus bookstores, so we suggest you order it from your favorite online purveyor.

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
  • Athel Cornish-Bowden, Fundamentals of Enzyme Kinetics, 4th Edition (publisher's web site).

Course Outline (draft)

1Tuesday8/30/2016Intro to systems biologyLeepapers
Thursday9/1/2016Equilibrium Binding 1Faeder6.1-6.2Statistical mechanics: counting and the Boltzmann distribution.
Friday9/2/2016RecitationTAIntro to Matlab
2Tuesday9/6/2016Equilibrium Binding 2Faeder6.3-6.4Thermodynamics, law of Mass Action, Shannon entropy
Thursday9/8/2016Equilibrium Binding 3Faederreview Ch 5.Cooperative models of binding
Friday9/9/2016RecitationTAIntro to BioNetGen
3Tuesday9/13/2016Equilbrium Binding 4Faeder7.1-7.3Gibbs distribution, two-state models, cooperative binding, MWC
Thursday9/15/2016Biochemical Kinetics 1Faeder15.1-15.2
4Tuesday9/20/2016Transcriptional regulationFaeder19.1-19.2Regulated recruitment, lac operon
Thursday9/22/2016Dynamics of genetic circuits 1Faeder19.3.1-19.3.3Stochastic dynamics, chemical master equation, Gillespie algorithm, Fano factor
5Tuesday9/27/2016Dynamics of genetic circuits 2Faeder19.3.4-19.3.6Switches and oscillators
Thursday9/29/2016Modeling Cell Signaling 1Faeder19.4.1Bacterial chemotaxis, adaptation
Friday9/30/2016Modeling Cell Signaling 2TA19.4.2Avidity, immune receptor signaling, kinetic proofreading
6Tuesday10/4/2016Imaging 1Lee
Thursday10/6/2016Imaging 2Lee
7Tuesday10/11/2016Parameter Estimation 1PfenningTechniques for linear and non-linear models
Thursday10/13/2016Parameter Estimation 2PfenningLocal vs. global optimization
8Tuesday10/18/2016Learning Model Structure 1PfenningIntroduction to networks, graph theory, scale-free concepts
10/19/2016Project proposals due
Thursday10/20/2016Learning Model Structure 2PfenningCorrelation, Partial Correlation, Applications
Friday10/21/2016No recitationCMU Mid-semester break
9Tuesday10/25/2016Learning Model Structure 3PfenningBayesian Networks, Gene regulation
Thursday10/27/2016Comp Neuro 1PfenningNeurobiology Basics, Integrate and Fire Neurons
10Tuesday11/1/2016Comp Neuro 2PfenningAction Potential, Hodgekin Huxley Model
Thursday11/3/2016Comp Neuro 3PfenningMarkov Chain Models
11Tuesday11/8/2016Comp Neuro 4PfenningMarkov Model Applications, Neuron firing + song behavior
Thursday11/10/2016Comp Neuro 5PfenningPoisson Process, Model of neuron firing
12Tuesday11/15/2016Populations models and evolution 1PfenningDeterministic and stochastic populations models
Thursday11/17/2016Populations models and evolution 2PfenningDNA Sequence Evolution, Evolution invasive analysis
13Tuesday11/22/2016No classThanksgiving
Thursday11/24/2016No classThanksgiving
Friday11/25/2016No recitationTAThanksgiving
Friday12/2/2016Final Projects Due
15Tuesday12/6/2016TBDPreliminary project scores due
Friday12/9/2016Project reviewing
16Friday12/9/2016Take home exam distributed
Wednesday12/14/2016Take home exam due
Wednesday12/21/2016Final Grades Due

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