SimPep and OP-AND: A deep learning framework and curated database for predicting osteogenic peptides

doi:10.1371/journal.pcbi.1013422

SimPep and OP-AND: A deep learning framework and curated database for predicting osteogenic peptides

Fig 2

The architecture of SimPep-Net model.

(A) A pair of peptides is provided as input to SimPep-Net, with each peptide encoded to a 1024-dimensional vector using the pre-trained ProtBERT model ( and , (B) Each vector is mapped individually to a 32-dimensional ( and latent space via a non-linear function , (C) The absolute difference between the two latent vectors is computed and passed through a fully connected layer with 16 neurons followed by a sigmoid activation to predict peptide similarity.

doi: https://doi.org/10.1371/journal.pcbi.1013422.g002