ProTAMAR for identifying the torsion angle of protein sequences
The torsion angle of proteins controls the spatial conformation and function of proteins.To improve the performance of torsion angle prediction of protein sequences,a new deep learning model,ProTAMAR,is proposed.Based on the traditional protein sequence coding and multiple sequence comparison results,a protein pre-training coding is introduced to capture high-dimensional feature representation,and a multi-headed attention mechanism and a dilated convolution module are designed for extracting global sequence information and local contextual information.The ProTAMAR model is tested extensively in protein benchmark datasets with excellent results.It is experimentally confirmed that the pre-trained features designed and the network framework introduced in this paper provide more valuable biological cues and more efficient extraction for protein sequence torsion angle prediction tasks.
NETL
NSTL
万方数据
维普
