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- YAMASHITA Yoshiharu
- Graduate School of Science and Engineering, Ritsumeikan University
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- SOEJIMA Naoki
- Graduate School of Science and Engineering, Ritsumeikan University
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- KAWABATA Masanari
- College of Life Science, Ritsumeikan University
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- Punzalan Florencio Rusty
- Graduate School of Science and Engineering, Ritsumeikan University
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- SHIMAYOSHI Takao
- ASTEM Research Institute of Kyoto
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- KUWABARA Hiroaki
- College of Information Science and Engineering, Ritsumeikan University
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- KUNIEDA Yoshitoshi
- College of Information Science and Engineering, Ritsumeikan University
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- AMANO Akira
- College of Life Science, Ritsumeikan University
Bibliographic Information
- Other Title
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- 形式的に記述されたODE解法スキームに基づくCellMLシミュレーションコード生成システム
- ケイシキテキ ニ キジュツ サレタ ODEカイホウ スキーム ニ モトズク CellML シミュレーションコード セイセイ システム
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Description
Physiology models written in a description language such as CellML are becoming a popular method to handle complex cellular physiological models in biological function simulations. However, in order to fully simulate a model, boundary conditions and ordinary differential equation (ODE) solving schemes have to be combined with it. Though the former can be described in CellML, it is difficult to explicitly specify ODE solving schemes using existing tools. In this study, we defined an ODE solving scheme description language based on XML and proposed a code generation system for biological function simulations. By using the proposed system, biological simulation programs using various ODE solving schemes can be easily generated. We designed a two-stage approach where the system generates a set of equation associating with the physiological model variable values at a certain time t with values at t plus delta t in the first stage and generates the programs calculating the time evolution of the model in the second stage. This approach enables the flexible construction of code generation modules that can support complex sets of formulas. We evaluated the relationship between models and their calculation accuracies by simulating complex biological models using various ODE solving schemes. Using the FHN model simulation, results showed good qualitative and quantitative correspondence with the theoretical predictions. Results for the LuoRudy1991 model showed that only first order precision was achieved. In addition, running the generated code in parallel on GPU made it possible to speed up the calculations by a factor of 50.
Journal
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- Transactions of Japanese Society for Medical and Biological Engineering
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Transactions of Japanese Society for Medical and Biological Engineering 50 (1), 68-77, 2012
Japanese Society for Medical and Biological Engineering
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Keywords
Details 詳細情報について
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- CRID
- 1390282680243643008
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- NII Article ID
- 40019319100
- 130004494160
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- NII Book ID
- AA11633569
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- ISSN
- 18814379
- 1347443X
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- NDL BIB ID
- 023766292
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed