Jun 18, 2024 · The results suggest that predicting enhancer–promoter interactions (EPIs) on other cell lines based solely on the sequence perspective of a specific cell line ...

May 18, 2024 · Hence, this article proposes the PDCNN model, a deep learning-based enhancer prediction method. PDCNN extracts statistical nucleotide representations from gene ...

Nov 1, 2023 · These statistical methods can be used to identify different types of genomic elements, such as exons, introns, promoters, enhancers, positioned nucleosomes, ...

Mar 13, 2024 · This method effectively predicts the genomic locations where known transcription factors (TFs) with binding sequence motifs are likely to interact. However, it ...

Dec 12, 2023 · Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states ...

May 23, 2024 · Additionally, we demonstrated methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel ...

Feb 29, 2024 · Identification of promoters, enhancers, and their interactions helps understand genetic regulation. This study proposes a graph-based semi-supervised ...

Apr 17, 2024 · Predicting enhancers and promoters directly from DNA sequences is believed to be more applicable than identifying them from multiple epigenomic features because ...

Nov 16, 2023 · Here we present elucidating the utility of genomic elements with neural nets (EUGENe), a FAIR toolkit for the analysis of genomic sequences with deep learning.

Jul 19, 2023 · Our study comprehensively identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and ...