Hunt C Anthony, Erdemir Ahmet, Lytton William W, Gabhann Feilim Mac, Sander Edward A, Transtrum Mark K, Mulugeta Lealem
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94143, USA.
Department of Biomedical Engineering and Computational Biomodeling Core, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
Processes (Basel). 2018 May;6(5). doi: 10.3390/pr6050056. Epub 2018 May 14.
Developing and improving mechanism-oriented computational models to better explain biological phenomena is a dynamic and expanding frontier. As the complexity of targeted phenomena has increased, so too has the diversity in methods and terminologies, often at the expense of clarity, which can make reproduction challenging, even problematic. To encourage improved semantic and methodological clarity, we describe the spectrum of Mechanism-oriented Models being used to develop explanations of biological phenomena. We cluster explanations of phenomena into three broad groups. We then expand them into seven workflow-related model types having distinguishable features. We name each type and illustrate with examples drawn from the literature. These model types may contribute to the foundation of an ontology of mechanism-based biomedical simulation research. We show that the different model types manifest and exert their scientific usefulness by enhancing and extending different forms and degrees of explanation. The process starts with knowledge about the phenomenon and continues with explanatory and mathematical descriptions. Those descriptions are transformed into software and used to perform experimental explorations by running and examining simulation output. The credibility of inferences is thus linked to having easy access to the scientific and technical provenance from each workflow stage.
开发和改进面向机制的计算模型以更好地解释生物现象是一个动态且不断扩展的前沿领域。随着目标现象的复杂性增加,方法和术语的多样性也随之增加,这往往是以清晰度为代价的,这可能使重现具有挑战性,甚至产生问题。为了促进语义和方法的清晰度提高,我们描述了用于构建生物现象解释的面向机制模型的范围。我们将现象的解释分为三大类。然后将它们扩展为具有可区分特征的七种与工作流程相关的模型类型。我们为每种类型命名并用文献中的例子进行说明。这些模型类型可能有助于基于机制的生物医学模拟研究本体的基础构建。我们表明,不同的模型类型通过增强和扩展不同形式和程度的解释来体现并发挥其科学效用。这个过程从关于现象的知识开始,接着是解释性和数学描述。这些描述被转化为软件,并通过运行和检查模拟输出用于进行实验探索。因此,推理的可信度与能够轻松获取每个工作流程阶段的科学和技术来源相关联。