Here you can defined how your predcitor dataset should look like. Principle Predictors can be added by CDK [1] or via the HMDB [2] database. Keep in mind that predictors that have zero to none variance are excluded before training the regression model.
This option calculates 291 precitors by using the R-Wrapper package RCDK [3]. For this option you need to provide SMILES with your data. For further details about this predictor set, see: https://egonw.github.io/cdkbook/appmoldescs.html#molecular-descriptors
The HMDB provides a wide variety of information for metabolomic researchers, this software utilizes the provided predicted molecular properties. For this option you need to provide the HMDB ID's with your data.
[1] Willighagen et al. The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching. J. Cheminform. 2017; 9(3) [2] Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, et al., HMDB 4.0 — The Human Metabolome Database for 2018. Nucleic Acids Res. 2018. Jan 4;46(D1):D608-17 [3] Guha, R. (2007). 'Chemical Informatics Functionality in R'. Journal of Statistical Software 6(18)
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