Modeling and simulation of biochemical networks has become an essential activity to aid in the understanding of cellular behavior and to facilitate quantitative interpretation of modern experiments. A new approach, "systems biology", is being advocated which combines modeling, simulation and quantitative experiments. Biomedical research is becoming increasingly dependent on construction and simulation of computational models. Arguably this will be even more the case with the development of personalized medicine. However, the technical aspects of modeling and simulation are overwhelming to a large number of biomedical researchers, and what is needed is a software application that is capable of providing the appropriate numerical algorithms shielded by a user interface that aides the biomedical researcher to conduct the required simulations. We propose to address this need with continuing development of our software COPASI, which is already widely used in the research community. This project will also provide support to the vibrant community of COPASI users/biomedical researchers. We will address this with the following Specific Aims:
Aim 1 : Enable COPASI with new functionality to provide advanced model capabilities by adding support for models containing noise and explicit time delays. Support for 1 and 2 dimensional compartments (filaments and membranes) will be implementes as well as support for discrete events in stochastic and delay differential simulation algorithms.
Aim 2. Improve and extend interoperability and standards compliance. COPASI will be equipped to facilitate users to create and read simulation information in SED-ML format, it will be enabled to save and read simulation and experimental result in the SBRML format, and it will support the proposed SBML Level 3.
Aim 3. Software maintenance. An existing testing plan will be continued and expanded, including appropriate collection models designed to test the various functions of the software;bug reports will be collected and fixed;suggestions for improvement will be collected from users and followed through.
Aim 4. Support the modeling community. Online support will be developed and maintained, such as video tutorials, user forum, user manual, and frequently asked questions. A COPASI User's Workshop will be held annually.

Public Health Relevance

This research will focus on developing and maintaining a computational tool, COPASI, for studying complex biological systems, including human disease models. This software application will facilitate knowledge discovery using computer simulations that are important in health and disease, including drug design. Use of this software will be available to all biomedical researchers and will contribute to understanding how diseases develop and how they can be cured.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM080219-05A1
Application #
8237359
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Lyster, Peter
Project Start
2007-09-01
Project End
2016-05-31
Budget Start
2012-09-15
Budget End
2013-05-31
Support Year
5
Fiscal Year
2012
Total Cost
$343,463
Indirect Cost
$127,028
Name
Virginia Polytechnic Institute and State University
Department
None
Type
Organized Research Units
DUNS #
003137015
City
Blacksburg
State
VA
Country
United States
Zip Code
24061
Tapinos, Avraam; Mendes, Pedro (2013) A method for comparing multivariate time series with different dimensions. PLoS One 8:e54201
Thiele, Ines; Swainston, Neil; Fleming, Ronan M T et al. (2013) A community-driven global reconstruction of human metabolism. Nat Biotechnol 31:419-25
Mitchell, Simon; Mendes, Pedro (2013) A computational model of liver iron metabolism. PLoS Comput Biol 9:e1003299
Swainston, Neil; Mendes, Pedro; Kell, Douglas B (2013) An analysis of a 'community-driven' reconstruction of the human metabolic network. Metabolomics 9:757-764
Smallbone, Kieran; Messiha, Hanan L; Carroll, Kathleen M et al. (2013) A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes. FEBS Lett 587:2832-41
Kent, Edward; Neumann, Stefan; Kummer, Ursula et al. (2013) What can we learn from global sensitivity analysis of biochemical systems? PLoS One 8:e79244
Mendes, Pedro; Hoops, Stefan; Sahle, Sven et al. (2009) Computational modeling of biochemical networks using COPASI. Methods Mol Biol 500:17-59
Mendes, Pedro; Messiha, Hanan; Malys, Naglis et al. (2009) Enzyme kinetics and computational modeling for systems biology. Methods Enzymol 467:583-99
Laubenbacher, Reinhard; Hower, Valerie; Jarrah, Abdul et al. (2009) A systems biology view of cancer. Biochim Biophys Acta 1796:129-39
Hower, Valerie; Mendes, Pedro; Torti, Frank M et al. (2009) A general map of iron metabolism and tissue-specific subnetworks. Mol Biosyst 5:422-43

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