Neal Maxwell Lewis, Gennari John H, Arts Theo, Cook Daniel L
Biomedical & Health Informatics, University of Washington, Seattle, WA 98195, USA.
Pac Symp Biocomput. 2009:304-15.
As a case-study of biosimulation model integration, we describe our experiences applying the SemSim methodology to integrate independently-developed, multiscale models of cardiac circulation. In particular, we have integrated the CircAdapt model (written by T. Arts for MATLAB) of an adapting vascular segment with a cardiovascular system model (written by M. Neal for JSim). We report on three results from the model integration experience. First, models should be explicit about simulations that occur on different time scales. Second, data structures and naming conventions used to represent model variables may not translate across simulation languages. Finally, identifying the dependencies among model variables is a non-trivial task. We claim that these challenges will appear whenever researchers attempt to integrate models from others, especially when those models are written in a procedural style (using MATLAB, Fortran, etc.) rather than a declarative format (as supported by languages like SBML, CellML or JSim's MML).
作为生物模拟模型整合的一个案例研究，我们描述了应用SemSim方法来整合自主开发的心脏循环多尺度模型的经验。具体而言，我们将一个适应性血管段的CircAdapt模型（由T. Arts用MATLAB编写）与一个心血管系统模型（由M. Neal用JSim编写）进行了整合。我们报告了模型整合经验带来的三个结果。第一，模型应明确不同时间尺度上发生的模拟。第二，用于表示模型变量的数据结构和命名约定可能无法在不同的模拟语言之间转换。最后，识别模型变量之间的依赖性是一项艰巨的任务。我们认为，每当研究人员试图整合来自他人的模型时，这些挑战都会出现，尤其是当这些模型采用过程式风格（使用MATLAB、Fortran等）编写而不是声明式格式（如SBML、CellML或JSim的MML等语言所支持的格式）时。
