Otto-von-Guericke-Universität Magdeburg


Pre-conference Workshops

General information

Workshop 1: 

Optimization in Systems and Synthetic biology: Concepts, methods and illustrative examples 

Irene Otero-Muras, Eva Balsa-Canto, Julio R. Banga
(Bio)Process Engineering Group, IIM-CSIC, Vigo-Spain 

Mathematical optimization is at the core of many problems in systems biology and synthetics biology: i) as the underlying hypothesis for model development, ii) in model identification, iii) in the computation of optimal stimulation procedures to synthetically achieve a desired biological behaviour or iv) in the design of biological circuits. Most of these problems are usually formulated as (multi-)objective non- linear programming problems with dynamic and algebraic constraints whose solution requires of specific numerical tools. This workshop is organized in three modules:
  • Optimization basics 
  • Optimization for the modelling in biological systems 
  • Optimization for the design of biological circuits 

Optimization basics

This module is intended to introduce basic concepts to the definition and solution of a non-linear constrained optimization problem. These will include mathematical problem formulation, types of optimization problems, optimality conditions, role of linear and non-linear constraints and basics on iterative local and global optimization methods to solve optimization problems. Multi-objective problems and their peculiarities will be also introduced. Theory will be accompanied by illustrative examples (convex, non-convex and unconstrained and constrained cases). 

Optimization for modelling of biological systems 

Optimization as the underlying hypothesis for modelling

Mathematical optimization is the underlying hypothesis for model development in for example (dynamic) flux balance analysis or the activation of metabolic pathways. These problems can be formulated as general dynamic optimization problems. In the first part of this module we will introduce the mathematical formulation and numerical approaches to deal with this type of problems. Concepts will be illustrated with examples related to the modelling of the bacterial diauxic growth or the just in time enzyme activation in simple metabolic networks.

Optimization as the basic tool for model identification

Modern experimental techniques can be used to obtain time-series data for the biological system under consideration. The goal of model identification is to characterize the model structure and to estimate the non-measurable parameters so as to reproduce, insofar as is possible, the experimental data. This section will present a brief overview of the role of optimization in parameter estimation and optimal model-based experimental design. We will use examples related to biological networks to illustrate different concepts. 

Optimization for the design of biological circuits

In this module, we will introduce optimization-based algorithms for the automated design of biological circuits. First, we will illustrate the capacities of optimization based tools for the design of de novo circuits with predefined performance, as part of the forward design cycle in Synthetic Biology. This section will cover:

  • Formulation and efficient solution of the biocircuit design problem, taking into account plug-and-play modularity and biological diversity (one functional behavior can be carried out by many different biological processes).
  • Multi-criteria design, introducing adapted multi-objective optimization techniques to find the Pareto sets of bio-circuits with best tradeoffs between a number of conflicting goals.

In a second part we will use optimization based frameworks for reverse design, identifying motifs performing a specific biological task, and helping to infer design principles of biological circuits. We will combine theory with practical examples, including the design of genetic switches and oscillators from a library of standard parts. 

Workshop 2

Kinetic and optimization­-based models for understanding the regulation of cellular metabolism

The ROBUSTYEAST consortium
Steffen Waldherr (OvGU Magdeburg / KU Leuven), Alexander Bockmayr (FU Berlin), Frank Bruggeman (VU Amsterdam), Vassily Hatzimanikatis (EPF Lausanne)

Constraint­-based models formulated as an optimization problem are an established framework to describe the metabolic behaviour of living cells. In such models, the biochemical reaction fluxes are modelled as optimization variables subject to biophysical constraints, and an optimization problem with a biologically reasonable objective is solved to obtain model predictions for the values of the fluxes. As an alternative model class, kinetic models explicitly include the regulation of reactions in the model description. Classically, this requires that all regulations, e.g., allosteric, are known for the model construction. However, new modeling approaches soften this requirement, enabling the construction of genome-scale kinetic models similar in scope to established constraint-based models. The proposed workshop focusses specifically on the interface between kinetic and optimization-based models to understand the regulation of cellular metabolism in a dynamic context.

The workshop is being organized by the ROBUSTYEAST consortium. ROBUSTYEAST is an European research consortium funded under the ERA­Net for Applied Systems Biology (ERASysAPP) program with the goal of revealing the engineering principles for robustness of metabolism to nutrient dynamics with yeast as a model organism. The connection between optimization­-based and kinetic models plays a crucial role in this, and the purpose of the workshop is to act as a platform for scientific exchange about the state of the art in this area between researchers within and outside the ROBUSTYEAST consortium.

There is also an invited session in the main conference program by the same organizers which builds upon this workshop. Details will be provided when the conference program has been finalized.

Workshop contributions

  • Henning Lindhorst, Otto-von-Guericke-University Magdeburg, DE: 
    “Optimization methods for metabolic networks – Cellular decision making by robust optimization”
  • Ronan Fleming, University of Luxembourg, LU:
    Variational kinetics: kinetic modelling based on variational analysis"

  • Ljubisa Miskovic, Georgios Fengos, Meric Ataman, Tuure Hameri, Vassily Hatzimanikatis, EPF Lausanne, CH:
    Kinetic modeling of genome­scale metabolic networks of E. coli and yeast without sacrificing stoichiometric, thermodynamic and physiological constraints

  • Panel discussion with the workshop contributors and the ROBUSTYEAST consortium about the connection between kinetic and optimization-based models.


Letzte Änderung: 07.10.2016 - Ansprechpartner: Webmaster
FOSBE 2016 on Twitter

Post and read news about #FOSBE2016 on Twitter!

FOSBE 2016 Secretariat

Laboratory for Systems Theory and Automatic Control
Otto von Guericke University Magdeburg
Universitätsplatz 2
39106 Magdeburg, Germany

Phone: +49 391 67 58577