Improving protein fold recognition using triplet network and ensemble deep learning.

ABSTRACT: Protein fold recognition is a critical step toward protein structure and function prediction, aiming at providing the most likely fold type of the query protein. In recent years, the development of deep learning (DL) technique has led to massive advances in this important field, and accordingly, the sensitivity of protein fold recognition has been dramatically improved. Most DL-based methods take an intermediate bottleneck layer as the feature representation of proteins with new fold types. However, this strategy is indirect, inefficient and conditional on the hypothesis that the bottleneck layer's representation is assumed as a good representation of proteins with new fold types. To address the above problem, in this work, we develop a new computational framework by combining triplet netw

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8768454 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature