Platform

Modeling / BioinformaticsCoordinator: Prof. E. D. Gilles

Presentation Heidelberg, July 7th 2004

Sven Sahle, EML research gGmbH

BMBF-Funding Initiative “Systems of Life – Systems Biology”

Humboldt University, Berlin:Prof. H.-G. Holzhütter, Charité, Mathematical

Modeling

Prof. R. Heinrich, Biology, Theoretical Biophysics

Prof. T. Höfer, Institute for Theoretical Biohysics

Prof. A. Herrmann, Biology, Molecular Biophysics

Prof. H. Herzel, Institute for Theoretical Biology

Prof. J. Reich, MDC for Molecular Medicine, Bioinformatics

EML Research, Heidelberg:Dr. U. Kummer, Bioinformatics and

Computational Biochemistry

Dr. R. Wade, Molecular and Cellular Modeling

MPI DCTS, Magdeburg:Prof. E.D. Gilles, Systems Biology

Prof. S. Schuster, Univ. Jena, Bioinformatics

Platform partners

Mission:

The platform “modeling/bioinformatics” is devoted to the development of methods and tools for the efficient construction, analysis, integration and exchange of complex mathematical models in systems biology.

The platform interacts with all partners of the initiative by:

•Providing novel methods and tools for the systems-level

analysis of the hepatocyte.

•Conducting specific research projects in cooperation with

the partners to develop methods, tools and standards.

Key objectives of research and development

• Unified methodology for the kinetic modeling of complex cellular networks encompassing metabolic, signal transduction and genetic sub-structures with a focus on network representation and complexity reduction.

• Novel methods for the analysis of complex networks based on systems theory regarding structural properties, network decomposition, identification of model structures, and others.

• New and/or improved computer tools for standardized modeling and simulation, including model and data storage.

• Integration of experimentation and modeling with respect to efficient experimental design and real-time control of biological processes.

Coordination of activities

• Distribution of tasks both in development of mehods/tools and research on cellular systems

• Progress meetings of the platform partners every 6 months.

• Annual international workshop `Modeling and simulation of complex biological systems´ open to all researchers within the BMBF initiative.

• Internal web portal for modeling and bioinformatics

Kinetic modeling of complex cellular networks with special focus on hepatocytes

I. Methods and tools

• Generalized control theory of cellular networks based on the well-established concept of metabolic control theory (Heinrich/Kacser).

• Standards for the formal and graphical representation of cellular networks.

• Theoretical framework for identification and evaluation of potential interfaces between various types of cellular networks.

• Inter-active software modules for computer simulations of hepatocyte-relevant kinetic models.

II. Modeling of selected sub-networks

…

Kinetic modeling of selected sub-networks: successive development of an

integrated model

Ca-mediated cell-cell

interactionexpression control of

metastasis genes

Wnt-ß-catenine signaling pathway

ubiquitin-dependent

protein turnover

metabolism and

biogenesis of lipoproteins

intra-cellular

lipid traffic

interfaces between the various modules of the integrative cell model

identification of potential oncogenes and tumor suppressor genes in signaling pathways

prediction of systemic effects upon administration of proteasome inhibitors

identification of target enzymes for the pharmacological treatment of disorders in the lipid metabolism of the liver

integrated kinetic model applications (examples)

project „vectorial transport through virtual hepatocytes” (Heidelberg)

cooperation

network project „systems biology of primary and regenerating hepatocytes (Freiburg)

cooperation

platform cell biology „3D bioartificial human liver cell systems“ (Berlin/Jena)

cooperation

Characterization of complex signaling and regulatory processes in hepatocytes using modeling and systems theory analysis

I. Methods and tools

• Modeling concepts for regulatory networks

• Visualization of models and simulations in ProMoT

• Structural analysis of signal transduction networks

• Software sensors for process control

II. Model-based analysis of selected sub-networks

• Mitogenic and apoptotic signaling pathways

• Signal integration in proliferation control

Characterization of complex signaling and regulatory processes in hepatocytes using modeling and systems theory analysis

SYCAMORE

I. Evaluate and integrate existing methods

II. Develop new methods

• Complexity reduction of big models

• Hybrid simulation methods

• Structure based methods to compute kinetic constants

• Sensitivity analysis of higher order

• Semi-automatic generation of models from databases

III. Apply tools to selected sub-systems of the hepatocyte

Heidelberg Magdeburg Berlin All groups

Gene networks

Cell cycle regulation

Expression control of metastasis genes

Ubiquitin-dependent protein turnover

Signaling networks

Wnt/ß-catenine pathway

Ca-mediated cell-cell interactions

Mitogenic and apoptotic pathways

Ca-mediated cellular signal transduction

Metabolic networks

Metabolism and biogenesis of lipoproteins

Intracellular lipid transport

Cytochrome P450 enzyme systems

Modelingmethods

Networkanalysis

Computer-based tools

Models and experiments

Reduction of complex kinetic models

Further development of standards for model exchange (SBML)

Symbolic representation of elementary processes and networks

Identification and evaluation of interfaces between cellular networks

Generalized control theory for cellular networks

Structural analysis of regulatory networks

PROMOT/DIVAmodeling / model library, simulation,model analysis

Interactive software modules for computer simulation

SYCAMOREexpert system for mathematical modeling and experimental design

Parameter estimation from system data and protein structures

Software sensors for hepatocyte bioreactors

Model-based experimental design

Me

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sys

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COPASI a simulator for complex pathways

modelling

reporting

analysis

simulation

modelling

reporting

analysis

simulation

Traditional tools:

text editor

command line tool plotting tool (eg. gnuplot)

command line tool

COPASI will combine all this in one tool with a graphical user interface. Users of COPASI should be biochemists and biologists without expert knowledge about simulation methods.

-> promote methods of systems biology

modelling

reporting

analysis

simulation

How is the biochemical reaction network described in COPASI?

• there are some chemical species• species are involved in chemical reactions• reactions happen with a certain speed.• all this happens in a compartment (of the cell)

Compartments just have a Volume.

Species are contained in compartments. They have a concentration or particle number (which can be converted using the volume of the compartment)

modelling

reporting

analysis

simulation

Deterministic simulation

The model is converted to a set of differential equations. The simple example (A -> B, v = k*substrate/(kM+substrate)) will give:

dA/dt = -k*A(kM+A)

dB/dt = +k*A(kM+A)

These differential equations are then numerically integrated using the LSODA solver (Adams for nonstiff regions, Gear for stiff regions).

Some Details

• written in C++ using QT library• available for Linux, Unixes, MacOs X, and

Windows• will be free for academic use

COPASI is developed in cooperation with Pedro Mendes, Virginia Bioinformatics Institute, Blacksburg, USA

Conclusion:COPASI will be an easy to use tool including powerful standard methods of systems biology.

COPASI also acts as a framework for the new modelling, simulation, and analysis tools that are developed in the BCB group

SYCAMORE

SYCAMORE (Systems biology Computational Analysis and MOdelling Research Environment) is a project carried out at EML Research, Heidelberg with the following aims: • Build a suite of methods and tools to faciliate the integration of experimental and computational approaches • Support the user in the choice of appropriate computational tools to tackle a specific problem

SYCAMORE

In order to develop SYCAMORE we need to

• Evaluate and integrate existing methods and

• Develop new methods in

• Complexity reduction of big models• Hybrid simulation methods• Structure based methods to compute kinetic constants• Sensitivity analysis of higher order• Semi-automatic generation of models from databases

SYCAMORE SYCAMORE architecture: