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Figure S2 Statistical model fits for Morgan based SEA on the random background data set create from ChEMBL 19. Figure S3 Z-score distribution (Morgan fingerprint) of the random background data set created from ChEMBL 19 database.

As benchmark data set, we chose the publicly available ChemDB random background data set published in the virtual screening study by Nasr et al. [28].

We built three data sets to construct the DNA duplex stability priors: one positive single-strand binding data set, one positive double-strand binding data set, and one background data set.

All the methods were assessed and compared for their ability to retrieve members of the same family against the background data set by using several performance metrics including the Area Under the Accumulation Curve (AUAC), Area Under the Curve (AUC), F1-measure, and BEDROC metrics.

Although the standard background data set for motif finding is promoter regions, this was not appropriate for the ZNF274 peak analysis.

Table 1 shows that for some of the compartments enriched among the proteins in the MHCII data set ('membrane' and 'extracellular region'), we observe lower fractions among the proteins in the MHCI data set than in the entire human proteome as estimated from the fractions of the background data set.

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Fourteen different multiple-molecule query methods were defined and benchmarked using: (1) 41 publicly available data sets of related molecules with similar biological activity; and (2) publicly available background data sets consisting of up to 175,000 molecules randomly extracted from the ChemDB database and other sources.

First, we employed the 17 MUV data sets compiled by Rohrer et al. [11] with their corresponding background data sets.

It should be noted that GOCE-DIR1, 2 and 3 are different in terms of the background data sets involved.

Tables 5 and 6 show the difference, averaged across the ChemDB background data sets and the MUV data sets respectively, between each method and the best performing method.

As described in Fig.  1, after data curation, the background data sets were randomly created with set sizes ranging from 10 to 1000 and an interval step of 10, which results in 4950 pairs of molecular data set.

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