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
Teaching AssistantsShe Zhang  shz66@pitt.edu  Office hours: cubicles on 3rd floor of BST3 (Biomedical Science Tower) Course DescriptionCMU 02730 & 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 handson experience with methods and models presented in class. Course requirements include weekly homework assignments, a final project, and a takehome exam. PrerequisitesThe
course is designed for graduate and upperlevel undergraduate students
with a wide variety of backgrounds. The course is intended to be
selfcontained 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 midsemester. See Proposals for more information.
 The project will be graded by peerreview 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 reuse 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.
 TakeHome Exam (30%)
 One week for a problem set covering course topics.
Meeting TimesFirst day of class: Tuesday, August 30, 2016. Lectures: Tu,Th 1:302:50 pm, SCG 103*
Lab: Fr 1:303:30pm, SCG 110*
*Note: These rooms are in the Pittsburgh Supercomputing Center, 300 S. Craig Street. (directions) Required TextPhysical Biology of the Cell, 2nd edition (PBOC). Reading and homework assignments will be drawn from this book. It has not been preordered at campus bookstores, so we suggest you order it from your favorite online purveyor. Recommended TextsThe 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, ISBN13: 9781584886426.
 Chris Myers, Engineering Genetic Circuits, Chapman and Hall/CRC, ISBN13: 9781420083248.
 E. Klipp, R. Herwig, A. Kowald, C. Wierling, and H. Lehrach, Systems Biology in Practice: Concepts, Implementation, and Application, WileyVCH, ISBN13: 9783527310784. (Note: an updated version called Systems Biology: A Textbook is also now available.)
 D. Kaplan and L. Glass, Understanding Nonlinear Dynamics. Springer. 1995. ISBN13: 9780387944401.
 Eberhard Voit, A First Course in Systems Biology, Garland Science. 2012. ISBN13: 9780815344674
 Sarah Otto and Troy Day, A Biologist's Guide to Mathematical Modeling in Ecology and Evolution, Princeton University Press, ISBN13: 9780691123448
 Athel CornishBowden, Fundamentals of Enzyme Kinetics, 4th Edition (publisher's web site).
Course Outline (draft)Week  Day  Date  Title  Presenter  Reading  Topics  1  Tuesday  8/30/2016  Intro to systems biology  Lee  papers    Thursday  9/1/2016  Equilibrium Binding 1  Faeder  6.16.2  Statistical mechanics: counting and the Boltzmann distribution.   Friday  9/2/2016  Recitation  Zhang   Intro to Matlab  2  Tuesday  9/6/2016  Equilibrium Binding 2  Faeder  6.36.4  Thermodynamics, law of Mass Action, Shannon entropy   Thursday  9/8/2016  Equilibrium Binding 3  Faeder     Friday  9/9/2016  Recitation  Zhang   Intro to BioNetGen  3  Tuesday  9/13/2016  Equilibrium Binding 4  Faeder  7.17.3  Cooperativity, twostate systems, MWC model   Thursday  9/15/2016  Biochemical Kinetics 1  Faeder  15.115.2    Friday  9/16/2016  Recitation  Zhang   Intro to parameter estimation  4  Tuesday  9/20/2016  Enzyme catalysis and steady state approximation  Faeder  15.2  Approach to equilibrium, MichaelisMenten dynamics, validity of the steady state approximation   Thursday  9/22/2016  Phosphorylation cascades and ultrasensitivity  Faeder  15.2.6  Multisite phosphorylation, GoldbeterKoshland mechanism for zeroth order ultrasensitivity   Friday  9/23/2016  Recitation  Zhang   Class and homework review  5  Tuesday  9/27/2016  Bifurcation analysis in 1D  Faeder  Lisman, 1985  Autophosphorylating kinase, autoregulated gene   Thursday  9/29/2016  Stochastic Chemical Kinetics  Faeder  19.3  Chemical Master Equation, Gillespie Algorithm,   Friday  9/30/2016  Recitation  Zhang   Coding Gillespie Direct in Matlab  6  Tuesday  10/4/2016  Networks 1  Pfenning   Principles of Biological Networks   Thursday  10/6/2016  Networks 2  Pfenning   Network Motifs   Friday  10/7/2016  Recitation  Zhang   Constructing graphs in Matlab  7  Tuesday  10/11/2016  Analysis of 2D ODE systems 1  Faeder  15.2.6, 19.3.6  Linear systems and stability in 1D and 2D   Thursday  10/13/2016  Analysis of 2D ODE systems 2  Faeder  19.3.6  Hopf bifurcation, genetic toggle switch, genetic oscillator   Friday  10/14/2016  Recitation  Zhang   Using pplane for analysis of 2D ODEs  8  Tuesday  10/18/2016  Boolean modeling of cell circuits  MiskovZivanov   Guest lecture on application of Boolean modeling to biological networks    10/19/2016     Project proposals due   Thursday  10/20/2016  Dynamics of network motifs I  Lee   Autoregulation, incoherenet FFL's and adaptation, etc.   Friday  10/21/2016  No recitation    CMU Midsemester break  9  Tuesday  10/25/2016  Networks 3  Pfenning   Stimulus Response   Thursday  10/27/2016  Networks 4  Pfenning 
 Gaussian Graphical Models   Friday  10/28/2016  Recitation  Zhang   Homework review  10  Tuesday  11/1/2016  Networks 5  Pfenning   Bayesian Networks
  Thursday  11/3/2016  Dynamics of transcriptional motifs II  Lee   Review of network motifs, perception and Weber's law, fold change detection, NFkB signaling   Friday  11/4/2016  Recitation  Zhang   Homework questions  11  Tuesday  11/8/2016  Computational Neuroscience I  Pfenning  7.1, 17.117.3  Neuroscience and Ion Channels   Thursday  11/10/2016  Computational Neuroscience II  Pfenning  17
 Action Potentials   Friday  11/11/2016  Recitation  Zhang   Class and homework review  12  Tuesday  11/15/2016  Jean Yang Guest Lecture  Yang   Deterministic and stochastic populations models   Thursday  11/17/2016  Computational Neuroscience III  Pfenning 
 Neural Communication   Friday  11/18/2016  Recitation  Zhang   Homework review  13  Tuesday  11/22/2016  No class    Thanksgiving   Thursday  11/24/2016  No class    Thanksgiving   Friday  11/25/2016  No recitation  Zhang   Thanksgiving  14  Tuesday  11/29/2016  A sensory circuit in action: E. coli chemotaxis  Faeder   Biased random walks, chemotaxis receptors and two component signaling, integral feedback control and perfect adaptation   Thursday  12/1/2016  Modeling cell signaling  Faeder   Rulebased modeling, receptor signaling, kinetic proofreading, modeling signaling complexes   Friday  12/2/2016     Final Projects Due  15  Tuesday  12/6/2016  Project reviewing    Preliminary project scores due   Thursday  12/8/2016  Project reviewing      Friday  12/9/2016      16  Friday  12/9/2016     Take home exam distributed   Wednesday  12/14/2016     Take home exam due   Wednesday  12/21/2016     Final Grades Due        
