Fig. 1

The flowchart of proposed IPMiner. It proceeded in two main steps. a Train stacked autoencoder models for RNA and protein, respectively, and fine tuning for it using label information from RNA-protein pairs. b Apply stacked ensembling to integrate SDA-RF, SDA-TF-RF and RPISeq-RF, which used high-level features before fine tuning, high-level features after fine tuning and raw k-mer frequency features, respectively. The network architectures were 256-128-64 with 256, 128, and 64 neurons in 3 hidden layers for stacked autoencoder