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 many biomedical researchers. What is needed is a software application capable of providing the appropriate numerical algorithms, but shielded by a user interface that aides the biomedical researcher in conducting the required simulations. Modeling and simulation can be applied at the level of molecules, their networks, cells, tissues and whole organisms. Sometimes several of these levels have to be represented in order to properly predict and understand health and disease. Thus models are becoming larger, multiscale, and require various different mathematical frameworks for simulation. We propose to address this need with continuing development of the COPASI software, which is already widely used in the biomedical research community, addressing the current trends. 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. Add new numerical simulation and analysis methods to further support biomedical research. We will develop and add new hybrid simulation algorithms to address models that require some of its parts to be simulated in different frameworks. We will add a new task to analyze parameter identifiability, which is very useful for finding out if the model and data are matched, or improvements need to be made in both.
Aim 2. Improve COPASI?s user interface and the interfaces with other software. We will improve the graphical user interface to allow it to efficiently manipulate very large models. We will create a new programming interface so that others can easily use COPASI?s functions from other programs.
Aim 3. Software maintenance and standards compliance. We will continue to maintain the software, correcting errors and making improvements, guided by feedback collected from its users. We will continue to implement standards compliance to ensure the software is interoperable with other applications.
Aim 4. Support the modeling community. We will continue outreach program activities aimed helping biomedical researchers make full use of the software?s capabilities. This includes continuing to offer tutorials, courses, and workshops? to create further training videos and to maintain a webbased discussion group.

Public Health Relevance

This research will focus on developing and maintaining the COPASI software, a tool for studying complex biological systems, including human disease models, through computer simulation. COPASI will facilitate knowledge discovery using computer simulations that are important in health and disease, including drug design, and personalized medicine. Use of this software will be available to all biomedical researchers without limitation 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 #
3R01GM080219-11S1
Application #
9702318
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
Project Start
2007-09-01
Project End
2020-07-31
Budget Start
2018-08-01
Budget End
2019-07-31
Support Year
11
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Virginia Polytechnic Institute and State University
Department
Type
Organized Research Units
DUNS #
003137015
City
Blacksburg
State
VA
Country
United States
Zip Code
24061
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Gupta, Abhishekh; Mendes, Pedro (2018) An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems. Computation (Basel) 6:
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Verma, Meghna; Erwin, Samantha; Abedi, Vida et al. (2017) Modeling the Mechanisms by Which HIV-Associated Immunosuppression Influences HPV Persistence at the Oral Mucosa. PLoS One 12:e0168133
Millard, Pierre; Smallbone, Kieran; Mendes, Pedro (2017) Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli. PLoS Comput Biol 13:e1005396
Dacheux, Estelle; Malys, Naglis; Meng, Xiang et al. (2017) Translation initiation events on structured eukaryotic mRNAs generate gene expression noise. Nucleic Acids Res 45:6981-6992
Meng, Xiang; Firczuk, Helena; Pietroni, Paola et al. (2017) Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis. Nucleic Acids Res 45:1015-1025
Swainston, Neil; Smallbone, Kieran; Hefzi, Hooman et al. (2016) Recon 2.2: from reconstruction to model of human metabolism. Metabolomics 12:109
Millard, Pierre; Portais, Jean-Charles; Mendes, Pedro (2015) Impact of kinetic isotope effects in isotopic studies of metabolic systems. BMC Syst Biol 9:64

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