This application, written in response to RFA-HL-07-002, entitled Modeling for Heart, Lung, and Blood: From Cell to Organ, is to provide training in computational modeling for investigators in the spirit of the Physiome effort, which has the goal of developing quantitative biology to improve medical science from genes to health. The program will consist of 2 courses per year, workshops at meetings, web tutorials and modeling, libraries of model programs and modeling systems for free distribution, and individual trainee follow-up training programs. The central mission is to aid investigators in developing expertise in the design of efficient experimental studies and in the analysis of data using integrative physiological models. The courses focus on applying the principles of the scientific method for designing and testing hypotheses and the use of parameterization and categorization of observations for diagnosis and therapy. The coverage ranges from the development of biophysical and biochemical level modules for cellular and subcellular systems, to whole body integrative systems for cardiovascular, respiratory and hematologic systems. Via hands on modeling from the first hour of the course using JSim a powerful but easily learned simulation system handling ordinary and partial differential equations (ODE and PDEs), stochastic models, etc., participants will learn how to examine data in order to develop hypotheses, how to convert ideas into mathematical testable model-hypotheses, how to evaluate the veracity and accuracy of computer solutions, how to design critical experiments using modeling, how to analyze data by optimization techniques providing residuals and confidence ranges for parameters, and how to evaluate validity of hypotheses and iterate the hypothesis-model- experiment-validation loop. Course participants will use software such as JSim, a platform-independent simulation analysis system, and Matlab. They will learn about simulation systems suitable for solving ODEs, Gepasi, XPPAUT, etc. and other tools, e.g. Systems Biology Workbench. Participants may also choose to return for individual training or for collaborative research. Each year the June course will emphasize elemental biophysical, physiological, and biochemical module design and construction, with application to clinical research using integrative models for positron emission tomography or magnetic resonance. Each year the September course will emphasize an application area such as cardiac or respiratory studies. Over the 4-year program we plan to provide courses and individual training for 200 participants to learn in depth, for others to train themselves using our models and tutorials on the web, and for any investigator to take these published models as starting points for their own models. The result should enhance our nation's capabilities in quantitative research analysis and improve our competitiveness in the advancement of diagnostic and therapeutic techniques.
| Raymond, G M; Bassingthwaighte, J B (2015) Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance. Br J Pharm Res 7:457-476 |
| Smith, Lucian P; Butterworth, Erik; Bassingthwaighte, James B et al. (2014) SBML and CellML translation in antimony and JSim. Bioinformatics 30:903-7 |
| Veress, A I; Raymond, G M; Gullberg, G T et al. (2013) Left ventricular finite element model bounded by a systemic circulation model. J Biomech Eng 135:54502 |
| Jardine, Bartholomew; Bassingthwaighte, James B (2013) Modeling serotonin uptake in the lung shows endothelial transporters dominate over cleft permeation. Am J Physiol Lung Cell Mol Physiol 305:L42-55 |
| Alessio, Adam M; Bassingthwaighte, James B; Glenny, Robb et al. (2013) Validation of an axially distributed model for quantification of myocardial blood flow using ¹³N-ammonia PET. J Nucl Cardiol 20:64-75 |
| Bassingthwaighte, James B; Chinn, Tamara M (2013) Reexamining Michaelis-Menten enzyme kinetics for xanthine oxidase. Adv Physiol Educ 37:37-48 |
| Bassingthwaighte, James B; Butterworth, Erik; Jardine, Bartholomew et al. (2012) Compartmental modeling in the analysis of biological systems. Methods Mol Biol 929:391-438 |
| Bassingthwaighte, James B; Beard, Daniel A; Carlson, Brian E et al. (2012) Modeling to link regional myocardial work, metabolism and blood flows. Ann Biomed Eng 40:2379-98 |
| Alessio, Adam M; Butterworth, Erik; Caldwell, James H et al. (2010) Quantitative imaging of coronary blood flow. Nano Rev 1: |
| Dash, Ranjan K; Bassingthwaighte, James B (2010) Erratum to: Blood HbO2 and HbCO2 dissociation curves at varied O2, CO2, pH, 2,3-DPG and temperature levels. Ann Biomed Eng 38:1683-701 |
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