BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches.

ABSTRACT: N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several experimental methods were used to identify DNA modifications. However, these experimental methods are costly and time-consuming. To detect the 6mA and complement these shortcomings of experimental methods, we proposed a novel, deep leaning approach called BERT6mA. To compare the BERT6mA with other deep learning approaches, we used the benchmark datasets including 11 species. The BERT6mA presented the highest AUCs in eight species in independent tests. Furthermore, BERT6mA showed higher and comparable performance with the state-of-the-art models while the BERT6mA showed poor performances in a few species with a small sample size. To overcome this is

SUBMITTER: Tsukiyama S 

PROVIDER: S-EPMC8921755 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature