Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.

ABSTRACT: As an essential task in protein structure and function prediction, protein fold recognition has attracted increasing attention. The majority of the existing machine learning-based protein fold recognition approaches strongly rely on handcrafted features, which depict the characteristics of different protein folds; however, effective feature extraction methods still represent the bottleneck for further performance improvement of protein fold recognition. As a powerful feature extractor, deep convolutional neural network (DCNN) can automatically extract discriminative features for fold recognition without human intervention, which has demonstrated an impressive performance on protein fold recognition. Despite the encouraging progress, DCNN often acts as a black box, and as such, it is challe

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8425391 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature