Figure 2.

Schematic framework of Meta-iAVP. Overview of the proposed methodology for discriminating AVPs from Non-AVPs involving the following steps: (1) preparing two benchmark datasets; (2) extracting a peptide sequence with five types of features to encode six models; (3) constructing six ML models to generate a six-dimentional feature for each type of feature O(M), where 1 and 0 are represented with AVPs and Non-AVPs, respectively; and (4) establishing the meta-predictor for each benchmark dataset that separates a query peptide into AVPs and Non-AVPs.