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Fig. 6 Chemical similarity method performance on hypothetical libraries of cyclic natural products.

Fig. 7 Chemical similarity method performance on hypothetical libraries of glycosylated natural products.

Fig. 4 Chemical similarity method performance on hypothetical libraries of linear products.

Fig. 8 Chemical similarity method performance on hypothetical libraries of complex hybrid natural products.

Fig. 3 Chemical similarity method performance on hypothetical libraries of linear peptides.

Chemical similarity method performance on hypothetical libraries of linear hybrid natural products with and without starter units.

To test how the proposed method performances on real data, we first applied it on a real tree genome dataset that has been used in [ 41], as a simplified example of metagenome data.

A summary of the methods' performance on NEMA IQ phantom data, based on different parameters, is shown in Figure 9.

Given the dependence of the methods' performance on lesion size, the data was divided into two size groups, large (17, 22, 28 and 37 mm) and small (10 and 13 mm), and average values were calculated for each group.

To test these methods' performance on biological data, a Arabidopsis L. Heynth dataset [18] of 800 genes and 22 time points is used.

We also measured the methods' performance on these data for a direct comparison to previous works.