Figure 1 Knowledge mining and interpretation workflows.
Increasingly complex high-dimensional PFC data create new challenges for data mining and interpretation.
For more information see also Additional file 1: Table S5 Many methods exist in the literature for the mining and interpretation of metabolomics data.
DG performed data mining and interpretation of expression data from testicular tumors and tumor icroenvironment and the comparison with gene expression of germ cells and Sertoli cells, and approved the final version of manuscript.
Tsai et al. [61] simplify the whole process into three parts (input, data analytics, and output) and seven steps (collection, selection, preprocessing, transformation, mining, evaluation, and interpretation).
The connectivity and interaction among the systems are analyzed by data mining, visualization and interpretation artefacts within a sustainability policy framework.
To make the discussions on the main operators of KDD process more concise, the following sections will focus on those depicted in Fig. 3, which were simplified to three parts (input, data analytics, and output) and seven operators (gathering, selection, preprocessing, transformation, data mining, evaluation, and interpretation).
The data mining and functional interpretation of datasets to access biologically interpretable results pose many analytical challenges, which have been recently reviewed by Kumar and Mann (2009).
Methods of natural language processing can be used to perform data mining and facilitate interpretation.
There is a one-to-one mapping between the bits and molecule features ideal for our mining and model interpretation.
The KDD process involves three main operations: selection and preparation of the data, data mining, and finally interpretation of the extracted units.
