We selected two AMP classification datasets from the literature, which we refer to as AMPScan and DeepAMP , in order to test the ability of approach to predict general antimicrobial activity. Detailed discussions on the creation of these datasets can be found in the original studies. The AMPScan and DeepAMP datasets contain 3556 and 3246 instances, respectively. Each dataset also contains a 50:50 ratio of AMPs to non-AMPs, allowing us to avoid issues that result from class imbalance. Associated to each dataset is a specific test set, and reporting results on this set allows comparison with the authors' proposed models. Despite being of similar size, one major differentiating factor between the two datasets is the length of peptides. Figure displays the empirical distribution of peptide lengths for both datasets. DeepAMP contains generally shorter peptides than AMPScan. Indeed, the DeepAMP dataset was curated since short-length AMPs have been shown to exhibit enhanced activity, lower toxicity and higher stability as opposed to their longer counterparts . More importantly, synthesis is cheaper for the short AMPs than the full-length AMPs, which increases the potential for clinical translation and commercialisation .