Protein Subcellular Localization Prediction by Combining ProtBert and BiGRU

The subcellular localization of proteins is very important for further understanding their functions. This paper proposes a deep learning method called PBLoc to predict the protein subcellular localization from sequence information only. In the PBLoc method, the pre-trained protein model–ProtBert, is utilized to extract the features of the protein sequence, followed by a bidirectional GRU model to predict subcellular localization. In order to capture sequence features more accurately, an attention mechanism is also used in the model. To verify the performance of our proposed PBLoc method, it is applied to DeepLoc benchmark dataset. For comparison, other 8 SOTA algorithms are also executed. The results show that PBLoc without using any evolution feature outperforms the other compared algorithms.