EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction.

ABSTRACT:

Background

Recognition of enhancer-promoter Interactions (EPIs) is crucial for human development. EPIs in the genome play a key role in regulating transcription. However, experimental approaches for classifying EPIs are too expensive in terms of effort, time, and resources. Therefore, more and more studies are being done on developing computational techniques, particularly using deep learning and other machine learning techniques, to address such problems. Unfortunately, the majority of current computational methods are based on convolutional neural networks, recurrent neural networks, or a combination of them, which don't take into consideration contextual details and the long-range interactions between the enhancer and promoter sequences. A new transformer-based model called EPI-

SUBMITTER: Ahmed FS 

PROVIDER: S-EPMC11184834 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature