iDNA6mA-Rice-DL

iDNA6mA-Rice-DL identifies DNA N6-methyladenine (6mA) sites in the rice genome to enable epigenetic and gene-regulation analyses.

Key Features:

• Deep Learning Framework: Employs a deep learning model with an embedding layer followed by multiple dense layers to automatically encode and extract DNA sequence features.
• High Accuracy and Performance: Validated on independent datasets with area under the ROC curve (auROC) of 0.98 and accuracy of 95.96% for predicting 6mA sites in rice.

Scientific Applications:

• Epigenetic Site Identification: Predicts DNA N6-methyladenine (6mA) modification sites in the rice genome for mapping methylation patterns.
• Plant Genomics and Gene Regulation: Supports studies of epigenetic modifications and their implications for gene regulation in rice and other plant genomes.

Methodology:

Processes DNA sequences with a deep learning architecture using an embedding layer and multiple dense layers to predict 6mA sites, with performance evaluated on independent datasets (auROC 0.98, accuracy 95.96%).