Gross Fridolin, MacLeod Miles
Institute for Philosophy, University of Kassel, Nora-Platiel-Strasse 1, 34127 Kassel, Germany.
Department of Philosophy, University of Twente, Drienerlolaan 5, 7522DN Enschede, The Netherlands.
Prog Biophys Mol Biol. 2017 Oct;129:3-12. doi: 10.1016/j.pbiomolbio.2017.01.003. Epub 2017 Jan 12.
There are currently no widely shared criteria by which to assess the validity of computational models in systems biology. Here we discuss the feasibility and desirability of implementing validation standards for modeling. Having such a standard would facilitate journal review, interdisciplinary collaboration, model exchange, and be especially relevant for applications close to medical practice. However, even though the production of predictively valid models is considered a central goal, in practice modeling in systems biology employs a variety of model structures and model-building practices. These serve a variety of purposes, many of which are heuristic and do not seem to require strict validation criteria and may even be restricted by them. Moreover, given the current situation in systems biology, implementing a validation standard would face serious technical obstacles mostly due to the quality of available empirical data. We advocate a cautious approach to standardization. However even though rigorous standardization seems premature at this point, raising the issue helps us develop better insights into the practices of systems biology and the technical problems modelers face validating models. Further it allows us to identify certain technical validation issues which hold regardless of modeling context and purpose. Informal guidelines could in fact play a role in the field by helping modelers handle these.
目前尚无广泛通用的标准来评估系统生物学中计算模型的有效性。在此，我们讨论为建模实施验证标准的可行性和必要性。拥有这样一个标准将有助于期刊评审、跨学科合作以及模型交换，并且对于接近医学实践的应用尤为重要。然而，尽管生成具有预测效度的模型被视为核心目标，但在实践中，系统生物学建模采用了多种模型结构和建模方法。这些方法服务于多种目的，其中许多是启发式的，似乎并不需要严格的验证标准，甚至可能会受到这些标准的限制。此外，鉴于系统生物学的现状，实施验证标准将面临严重的技术障碍，这主要归因于现有实验数据的质量。我们主张采取谨慎的标准化方法。然而，尽管此时进行严格标准化似乎为时过早，但提出这个问题有助于我们更好地洞察系统生物学的实践以及建模人员在验证模型时所面临的技术问题。此外，这使我们能够识别某些与建模背景和目的无关的技术验证问题。事实上，非正式指南可以通过帮助建模人员处理这些问题而在该领域发挥作用。
