PreRBP-TL is a new sequence-based computational predictor for identifying species-specific RNA-binding proteins (RBPs).
In which hybrid convolutional neural networks (CNNs) and transfer learning were employed.
The weights of prediction model were initialized by pre-training with the large general RBP dataset,
and then fine-tuned with the small species-specific RPB dataset by using transfer learning.
The experimental results show that the PreRBP-TL achieves obviously higher performance for identifying
the species-specific RBPs from six different organisms, outperforming eight
state-of-the-art computational methods, which is an important complement to existing methods.
The network architecture and framework of PreRBP-TL are shown in Fig. 1. For more information please refer to our paper.