Jim Faeder (University of Pittsburgh) - firstname.lastname@example.org - Office hours : after class or by appointment Robin Lee (University of Pittsburgh) - email@example.com - Office hours: after class or by appointment Andreas Pfenning (Carnegie Mellon University) - firstname.lastname@example.org - Office hours: after class or by appointment
She Zhang - email@example.com
- Office hours: cubicles on 3rd floor of BST3 (Biomedical Science Tower)
CMU 02-730 & PITT CMPBIO/MSCBIO 2040
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.
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.
- 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
- Take-Home Exam (30%)
- One week for a problem set covering course topics.
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)
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.
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)
|1||Tuesday||8/30/2016||Intro to systems biology||Lee||papers|
|Thursday||9/1/2016||Equilibrium Binding 1||Faeder||6.1-6.2||Statistical mechanics: counting and the Boltzmann distribution.|
|Friday||9/2/2016||Recitation||TA||Intro to Matlab|
|2||Tuesday||9/6/2016||Equilibrium Binding 2||Faeder||6.3-6.4||Thermodynamics, law of Mass Action, Shannon entropy|
|Thursday||9/8/2016||Equilibrium Binding 3||Faeder||review Ch 5.||Cooperative models of binding|
|Friday||9/9/2016||Recitation||TA||Intro to BioNetGen|
|3||Tuesday||9/13/2016||Equilbrium Binding 4||Faeder||7.1-7.3||Gibbs distribution, two-state models, cooperative binding, MWC|
|Thursday||9/15/2016||Biochemical Kinetics 1||Faeder||15.1-15.2|
|4||Tuesday||9/20/2016||Transcriptional regulation||Faeder||19.1-19.2||Regulated recruitment, lac operon|
|Thursday||9/22/2016||Dynamics of genetic circuits 1||Faeder||19.3.1-19.3.3||Stochastic dynamics, chemical master equation, Gillespie algorithm, Fano factor|
|5||Tuesday||9/27/2016||Dynamics of genetic circuits 2||Faeder||19.3.4-19.3.6||Switches and oscillators|
|Thursday||9/29/2016||Modeling Cell Signaling 1||Faeder||19.4.1||Bacterial chemotaxis, adaptation|
|Friday||9/30/2016||Modeling Cell Signaling 2||TA||19.4.2||Avidity, immune receptor signaling, kinetic proofreading|
|7||Tuesday||10/11/2016||Parameter Estimation 1||Pfenning||Techniques for linear and non-linear models|
|Thursday||10/13/2016||Parameter Estimation 2||Pfenning||Local vs. global optimization|
|8||Tuesday||10/18/2016||Learning Model Structure 1||Pfenning||Introduction to networks, graph theory, scale-free concepts|
|10/19/2016||Project proposals due|
|Thursday||10/20/2016||Learning Model Structure 2||Pfenning||Correlation, Partial Correlation, Applications|
|Friday||10/21/2016||No recitation||CMU Mid-semester break|
|9||Tuesday||10/25/2016||Learning Model Structure 3||Pfenning||Bayesian Networks, Gene regulation|
|Thursday||10/27/2016||Comp Neuro 1||Pfenning||Neurobiology Basics, Integrate and Fire Neurons|
|10||Tuesday||11/1/2016||Comp Neuro 2||Pfenning||Action Potential, Hodgekin Huxley Model|
|Thursday||11/3/2016||Comp Neuro 3||Pfenning||Markov Chain Models|
|11||Tuesday||11/8/2016||Comp Neuro 4||Pfenning||Markov Model Applications, Neuron firing + song behavior|
|Thursday||11/10/2016||Comp Neuro 5||Pfenning||Poisson Process, Model of neuron firing|
|12||Tuesday||11/15/2016||Populations models and evolution 1||Pfenning||Deterministic and stochastic populations models|
|Thursday||11/17/2016||Populations models and evolution 2||Pfenning||DNA Sequence Evolution, Evolution invasive analysis|
|Friday||12/2/2016||Final Projects Due|
|15||Tuesday||12/6/2016||TBD||Preliminary project scores due|
|16||Friday||12/9/2016||Take home exam distributed|
|Wednesday||12/14/2016||Take home exam due|
|Wednesday||12/21/2016||Final Grades Due|