Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.
Curr Med Chem. 2020;27(38):6444-6457. doi: 10.2174/0929867326666190801152317.
The KNIME platform offers several tools for the analysis of chem- and pharmacoinformatics data. Unless one has sufficient in-house data available for the analysis of interest, it is necessary to fetch third party data into KNIME. Many data sources offer valuable data, but including this data in a workflow is not always straightforward.
Here we discuss different ways of accessing public data sources. We give an overview of KNIME nodes for different sources, with references to available example workflows. For data sources with no individual KNIME node available, we present a general approach of accessing a web interface via KNIME. In addition, we discuss necessary steps before the data can be analysed, such as data curation, chemical standardisation and the merging of datasets.
KNIME 平台提供了多个用于分析化学和药物信息学数据的工具。除非有足够的内部数据可用于感兴趣的分析,否则有必要将第三方数据导入 KNIME。许多数据源提供了有价值的数据,但将这些数据包含在工作流程中并不总是那么简单。
在这里,我们讨论了访问公共数据源的不同方法。我们概述了适用于不同来源的 KNIME 节点,并提供了可用示例工作流程的参考。对于没有单独的 KNIME 节点可用的数据源,我们展示了通过 KNIME 访问 Web 界面的一般方法。此外,我们还讨论了在可以分析数据之前需要采取的步骤,例如数据管理、化学标准化和数据集的合并。