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Flexible informatics for linking experimental data to mathematical models via DataRail

机译:灵活的信息学,可通过DataRail将实验数据链接到数学模型

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Motivation: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results. Results: We describe the implementation of DataRail, an open source MATLAB-based toolbox that stores experimental data in flexible multi-dimensional arrays, transforms arrays so as to maximize information content, and then constructs models using internal or external tools. Data integrity is maintained via a containment hierarchy for arrays, imposition of a metadata standard based on a newly proposed MIDAS format, assignment of semantically typed universal identifiers, and implementation of a procedure for storing the history of all transformations with the array. We illustrate the utility of DataRail by processing a newly collected set of similar to 22 000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells.
机译:动机:由于缺乏合适的软件来管理和转换数据,因此无法将实验数据与生物学中的数学模型联系起来。如果可以保留与训练数据的链接以及用于从原始结果收集训练数据的所有归一化,缩放和融合例程的记录,则将有助于模型校准并增加模型的价值。结果:我们描述了DataRail的实现,DataRail是一个基于MATLAB的开源工具箱,该工具箱将实验数据存储在灵活的多维数组中,对数组进行转换以最大化信息内容,然后使用内部或外部工具构造模型。数据完整性是通过数组的包含层次结构,基于新提出的MIDAS格式强加元数据标准,分配语义类型的通用标识符以及存储与数组有关的所有转换历史记录的过程的实现来维护的。我们通过处理新收集的一组类似于从细胞因子刺激的原代和转化的人类肝细胞中获得的22,000种蛋白质活性测量值来说明DataRail的实用性。

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