A versatile platform for multilevel modeling of physiological systems

Published on November 4, 2014   33 min
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Hello, I’m Yoshiyuki Asai, a group leader of open biology unit in Okinawa Institute of Science and Technology, Japan. In this lecture I want to introduce a versatile platform for multilevel modeling of physiological systems. In recent biological and physiological research, computable mathematical models have
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become increasingly important for integrating the huge amount of knowledge and data obtained from experiments and simulations, and for applying simulation results to medicine. One of dream in such integrative physiology is to cause a paradigm shift from empirical medicine to predictive medicine.
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To promote effective collaborations to build large-scale models, it is also important to consolidate fundamental tools to support such activities. Model sharing and model reuse, which are crucial for the above-mentioned multidisciplinary collaborations, must be encouraged by using such tools. There have been several pioneering efforts to develop technologies in that direction such as SBML, CellML and PHML, among others. These are XML-based descriptive language-formats to describe the dynamics of biological and physiological systems. The main purpose of the development of these languages was to establish a common communication foundation to enhance the exchange of models among collaborators.
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Research in this kind of direction is sometimes referred to as Physiome, which is one of omics such as genome and proteome. It is considered that the first step what must be done in Physiome is to develop comprehensive methods for acquisition and databasing of very large sets of information on all aspects of biology to share and reuse the data among researchers. Then construct descriptive and quantitative models and organize collaborations.
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The target to understand and build a database is functions of living organisms. A physiological function is a change of the state of living organisms in time, that is dynamics of physiological state. It is impossible to store the dynamics in a database. Of course it is possible to store experimental time series data in a database, and it is important for physiome as the first step indeed. But such time series represents only one case of the dynamics of physiological function which happened under the experimental condition. Here physiologically plausible mathematical models play important roles. Since the models are symbolically written and so can be stored in databases. Besides, anytime we can take out the dynamics of the modeled function by numerical integration, i.e simulations. Even more importantly, by changing parameters, we can observe dynamics at the different conditions rather easily. Since the modeling target is ranging from molecular level up to individual level,
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variety of modeling techniques must be incorporated to build such multilevel models. For example, agent based systems are sometimes used for molecular dynamics simulation. Ordinary differential equations cover a wide range of dynamics such as membrane potential and walking motion. Of course partial differential equations and algebraic equations are also used. Since the modeling targets are multilevel to consider not only intra-level principles but also inter-level principles, these techniques are often used together in one model.
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The slide shows the entire scheme of our system including applications and databases. To support users to build such models of multilevel physiological systems, we have been developing PhysioDesigner on which users can make their own models. We also developed databases of models, and morphological and time series data. Models developed on PhysioDesigner are written in PHML format, which is an XML based model descriptive specification. And finally, simulations of those models are performed by Flint, a simulator supporting SBML as well as PHML.
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What is the benefit of using PhysioDesigner? Firstly it is possible to describe a model with the additional information, such as, article introducing the model, model creator, description of the model, and so on. Then the model would be a quit self-consistent. For example, when other researchers read the model, he or she can understand immediately what the model is, to who should have a contact, and so on. The second. On this platform, modeling and performing a simulation are completely separated. Modeling is done on PhysioDesigner, and simulation is done on Flint. This means that model creators can concentrate on modeling and logics to be modeled, and do not need to be bothered by programming, especially of implementation of numerical algorithm. This aspect becomes very important when one thinks of parallel computing. Usually it requires high programming skill to implement. Nowadays models tend to be progressively larger, parallel computing techniques becomes more important. The third point is about openness of the models. Sharing and reuse of models is crucial point to build a large scale multi level model. Of course people can share source codes of models even they use computer languages such as Java, C++ to build their models. But usually it is not easy to read source codes written by others. Moreover it is difficult to merge them into one model. PHML is a text format with tags, including a lot of additional information, which makes the model easier to read. Besides if models are opened, it is very easy to reproduce and validate the published simulation results. This enhances soundness of simulation research.
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A versatile platform for multilevel modeling of physiological systems

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