Fig. 4

The average Spearman’s correlation between the feature coefficients learned by multi-LRSL and feature data extracted from CTD for the same side effect is significantly bigger than random samples. The blue lines represent the density estimates for the averages of correlation coefficients of 1000 random samples. For each random sample, the average correlation is calculated with the same number of pairs of randomly selected feature coefficients and CTD feature data. The red arrows indicate the positions of the average correlation coefficients between paired feature coefficients and feature data (the frequency of features for chemical substructures, protein domains and gene ontology terms and the averages of gene expression changes). The p-values are estimated by Monte-Carlo test