Page tree
Skip to end of metadata
Go to start of metadata

Oberwolfach Seminar

19 – 25 November 2017

The seminar will include tutorial courses and modeling exercises focusing on the following topics:

  • different modeling paradigms for biological systems on the cellular level (ODEs, discrete dynamical systems, stochastic models), their advantages and disadvantages, challenges, and potential applications

  • property conservation across formalisms

  • parameter estimation and uncertainty quantification

The seminar takes place at the Mathematisches Forschungsinstitut Oberwolfach. The Institute covers board and lodging. By the support of the Carl Friedrich von Siemens Foundation travel expenses can be reimbursed up to 150 EUR in average per person (against copies of travel receipts). The number of participants is restricted to 25.

For organizational information see:

Applications should include

  • full name and university/institute address, e-mail address
  • short CV, present position, university
  • name of supervisor of Ph.D. thesis
  • a short summary of previous work and interest
  • title, ID and date of the intended seminar

and should be sent preferably by e-mail (with attachments in pdf format) to:

Prof. Dr. Dietmar Kröner
Mathematisches Forschungsinstitut Oberwolfach Schwarzwaldstr. 9 – 11
77709 Oberwolfach

Please bring

Recommended literature

  • P. Deuflhard and S. Röblitz. A Guide to Numerical Modelling in Systems Biology. Springer, 2015. Link
  • B. P. Ingalls. Mathematical Modeling in Systems Biology. MIT Press, 2013.
  • D. J. Wilkinson. Stochastic Modelling for Systems Biology. CRC Press, 2011.
  • R. Heinrich and S. Schuster. The Regulation of Cellular Systems. Chapman & Hall 1996.
  • B. O. Palsson. Systems Biology: Constraint-based Reconstruction and Analysis. Cambridge University Press 2015.
  • C. D. Maranas and A. R. Zomorrodi. Optimization Methods in Metabolic Networks. John Wiley & Sons 2016.
  • E. Klipp, R. Herwig, A. Kowald, C. Wierling, and H. Lehrach. Systems Biology in Practice. WILEY-VCH Verlag 2015. 

Preliminary Program

The Seminar will start on Sunday with a poster session, on Wednesday an excursion is planned. Departure is on Saturday. It is obligatory for all participants to attend the full program, a partial participation is not possible!

Sunday: Arrival and Poster Session

18:30-19:30   Dinner

20:00-21:30   Get-to-know Meeting and Poster Session

Monday: Discrete modelling

9:00-9:30       Introduction

9:30-11:00     Discrete modeling I: Basics Boolean modeling - mathematics and application

11:30-12:30   Discrete modeling II: Advanced analysis (Slides part 1 and part 2)

13:30-14:30   Advanced analysis (cont.), software introduction

15:00-17:00   Group work on different topics, e.g.,

  • case studies

  • math, methods and algorithms

  • software

17:00-17:30   Results preparation in the groups

17:30-18:15   Presentation and discussion

Tuesday: Metabolic networks

9:00  - 10:30    Biochemical reaction networks and mass balancing, stoichiometric analysis, quasi-steady state assumption (Slides part 1 [pdf])

11:00 - 12:30   Constrained based models: Optimization principle, flux balance analysis, dynamic flux balance analysis (Slides part 2 [pdf])

13:30 - 14:30   Matlab / Python toolboxes for metabolic network analysis

15:00 - 17:00   Group work:

17:00 - 17:30   Results preparation in the groups

17:30 - 18:15   Presentation and discussion of group work results

Wednesday: Regulatory and signaling pathways

9:00 - 10:30     Dynamics of regulatory and signaling pathways (ODE modelling: sensitivity, condition, stability, bifurcations), Slides

11:00 - 12:30   Stochastic chemical kinetics (Markov jump processes and the CME, rare events)

14:00 - 18:00   Excursion

Thursday: Parameter estimation

9:00 - 10:30    Parameter optimization:

  • Local and global search methods

  • Analysis of goodness-of-fit

11:00 - 12:30   Identifiability and uncertainty analysis:

  • Asymptotic methods

  • Profile likelihood

  • Markov-chain Monte-Carlo methods

Lecture slides:

14:00 - 14:30   Presentation of tasks for the group work on ODE and CME modelling

14:30 - 17:00   Group work

17:00 - 17:30   Results preparation in the groups

17:30 - 18:15   Presentation and discussion

Friday: Tutorial on parameter estimation and open problems

9:00 - 9:30     Presentation of tasks for the group work on parameter estimation and model selection

9:30 - 12:00   Group work: Parameter estimation and model selection

12:00 - 12:30   Results preparation in the groups

14:00 - 15:00   Presentation and discussion

15:00 - 17:00   Combining different modeling approaches & open problems

17:00 - 17:30   Wrap-up



Boolean modeling

Tutorial on Boolean modeling by R. Albert and J. Thakar 

Case studies 

Drug synergies in gastric cancer cells , here 

Signal-regulated GI/S transition, here

Signaling network regulating senescence, here

Math, methods, algorithms

Thomas Conjectures, here

Trap spaces, here or here

Attractor algorithms, here

Model sets and experimental design, here

Model inference,  here

Additional Software

 PyBoolNet, paper and download

BoolNet, paper and download

Regulatory and signaling pathways

Case studies / Computation 

The Schlögl model, here, paper

Gene-autoregulation, here

Predator-prey model, here

Michaelis-Menten kinetics, here, paper

SIR model, here

Toggle switch, here, paper

Network motives / Analysis

Bistability, paper

Oscillators, paper

Algorithms /Theory

Numerical continuation, here, books: Allgower/Georg (2003), Introduction to Numerical Continuation Methods;  Deuflhard (2005), Newton methods for nonlinear problems.

Solving the CME with the finite state projection method, here

Beyond SSA and tau-leaping, here

Hybrid models for chemical reaction kinetics, here


Parameter estimation and hypothesis testing

Computation / Impementation  

Parameter optization and profile likelihood calculation, here

Parameter estimation using Markov chain Monte Carlo sampling, here 

Modelling and parameter estimation for cancer signalling in COPASI, here

Theory / Methods

Identification of the governing equations of dynamical systems, here

Parameter estimation for stochastic / hybrid models using ABC, here

Advanced approaches for model selection, here


Software and tools, here




  • No labels