Leveraging the attention mechanism to improve the identification of DNA N6-methyladenine sites.

ABSTRACT: DNA N6-methyladenine is an important type of DNA modification that plays important roles in multiple biological processes. Despite the recent progress in developing DNA 6mA site prediction methods, several challenges remain to be addressed. For example, although the hand-crafted features are interpretable, they contain redundant information that may bias the model training and have a negative impact on the trained model. Furthermore, although deep learning (DL)-based models can perform feature extraction and classification automatically, they lack the interpretability of the crucial features learned by those models. As such, considerable research efforts have been focused on achieving the trade-off between the interpretability and straightforwardness of DL neural networks. In this study, w

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC8575024 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature