Modular Modeling of Cellular Systems with ProMoT/Diva

MOTIVATION Need for software to setup and analyze complex mathematical models for cellular systems in a modular way, that also integrates the experimental environment of the cells. RESULTS A computer framework is described which allows the building of modularly structured models using an abstract, modular and general modeling methodology. With this methodology, reusable modeling entities are introduced which lead to the development of a modeling library within the modeling tool ProMot. The simulation environment Diva is used for numerical analysis and parameter identification of the models. The simulation environment provides a number of tools and algorithms to simulate and analyze complex biochemical networks. The described tools are the first steps towards an integrated computer-based modeling, simulation and visualization environment Availability: Available on request to the authors. The software itself is free for scientific purposes but requires commercial libraries. SUPPLEMENTARY INFORMATION http://www.mpi-magdeburg.mpg.de/projects/promot

[1]  Axel Munack,et al.  On-Line Application of Parameter Estimation Accuracy to Biotechnical Processes , 1990, 1990 American Control Conference.

[2]  E. Gilles,et al.  The organization of metabolic reaction networks: a signal-oriented approach to cellular models. , 2000, Metabolic engineering.

[3]  E. Gilles,et al.  The organization of metabolic reaction networks. II. Signal processing in hierarchical structured functional units. , 2001, Metabolic engineering.

[4]  Ernst Dieter Gilles Network Theory for Chemical Processes , 1998 .

[5]  Julio Collado-Vides,et al.  RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12 , 2001, Nucleic Acids Res..

[6]  Daniel G. Bobrow,et al.  Book review: The Art of the MetaObject Protocol By Gregor Kiczales, Jim des Rivieres, Daniel G. and Bobrow(MIT Press, 1991) , 1991, SGAR.

[7]  D Weuster-Botz,et al.  Automated sampling device for monitoring intracellular metabolite dynamics. , 1999, Analytical biochemistry.

[8]  L M Loew,et al.  A general computational framework for modeling cellular structure and function. , 1997, Biophysical journal.

[9]  Igor Goryanin,et al.  Mathematical simulation and analysis of cellular metabolism and regulation , 1999, Bioinform..

[10]  P Mendes,et al.  Biochemistry by numbers: simulation of biochemical pathways with Gepasi 3. , 1997, Trends in biochemical sciences.

[11]  F. Neidhardt,et al.  Physiology of the bacterial cell : a molecular approach , 1990 .

[12]  Matthias Reuss,et al.  Optimal Experimental Design for Parameter Estimation in Unstructured Growth Models , 1994 .

[13]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[14]  E. Gilles,et al.  The organization of metabolic reaction networks. III. Application for diauxic growth on glucose and lactose. , 2001, Metabolic engineering.

[15]  Ernst Dieter Gilles,et al.  PROMOT: A Modeling Tool for Chemical Processes , 2000 .

[16]  Herbert M. Sauro,et al.  33 JARNAC: a system for interactive metabolic analysis , 2000 .

[17]  Stephen J. Wright,et al.  Optimization Software Guide , 1987 .

[18]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[19]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[20]  Michael Zeitz,et al.  DIVA - a simulation environment for chemical engineering applications , 1997 .

[21]  Masaru Tomita,et al.  E-CELL: software environment for whole-cell simulation , 1999, Bioinform..