Flexible informatics for linking experimental data to mathematical models via DataRail
Flexible informatics for linking experimental data to mathematical models via DataRail
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DOI：
10.1093/bioinformatics/btn018
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发表时间：
2008-03-01
期刊：
影响因子：
5.8
通讯作者：
Sorger, Peter K.
中科院分区：
文献类型：
--
作者：
Saez-Rodriguez, Julio;Goldsipe, Arthur;Sorger, Peter K.
动机：由于缺乏合适的软件来管理和转换数据，将实验数据与生物学数学模型联系起来受到阻碍。如果能够保留训练数据的链接以及用于从主要结果组装训练数据的所有归一化、缩放和融合例程的记录，则模型校准将变得更加容易，模型的价值也会增加。结果：我们描述了 DataRail 的实现，DataRail 是一个基于 MATLAB 的开源工具箱，它将实验数据存储在灵活的多维数组中，转换数组以最大化信息内容，然后使用内部或外部工具构建模型。通过数组的包含层次结构、基于新提出的 MIDAS 格式的元数据标准的实施、语义类型通用标识符的分配以及用于存储数组的所有转换的历史的过程的实现来维护数据完整性。我们通过处理一组新收集的类似于 22000 个从细胞因子刺激的原代和转化的人类肝细胞中获得的蛋白质活性测量值来说明 DataRail 的实用性。
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.