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Due to the difference in dataset setting, we cannot arbitrarily compare our results with the prior research results.
The possible explanation for this may lay in the difference in dataset selection.
However, the two orders of magnitude difference in dataset size (462 genes versus 10 proteins) made the standard correlation methods inapplicable.
The difference in dataset sample size is accounted for by the p-value assigned to the correlation coefficients, as smaller datasets would require a higher correlation coefficient between a pair of genes to match the p-value of lower coefficients in big datasets.
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To assess the statistical significance of the difference in datasets, the Student t-test was performed using the significance level of 0.05.
The difference in datasets also helps to prevent over-optimization of heuristic parameters.
Therefore, though the dataset varies across the 72 strategies, other factors beyond the difference in datasets are contributing substantially to the difference in results.
Interestingly, the influence of differences in dataset composition resulting from various ways of selection of molecules forming a set of inactives has never been thoroughly investigated.
The causes of the discrepancies between the plots for toy datasets and real-life datasets are based on the differences in dataset characteristics between toy datasets and real-life datasets.
In addition to differences in dataset sizes and composition, methodological differences between the family-centric and the PDM-based approach are likely to be responsible for the differences observed and the additional relevant families that were included in the PDMs.
The mean-centering method described in this study was used in a recent meta-analysis whilst our manuscript was under review [ 38], although no attempt was made to account for differences in dataset composition.
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