[HTML][HTML] Machine and deep learning methods for predicting 3D genome organization
Abstract Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter
interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B …
interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B …
MuSE: A deep learning model based on multi-feature fusion for super-enhancer prediction
W He, H Zhou, Y Zuo, Y Bai, F Guo - Computational Biology and Chemistry, 2024 - Elsevier
Although bioinformatics-based methods accurately identify SEs (Super-enhancers), the
results depend on feature design. It is foundational to representing biological sequences …
results depend on feature design. It is foundational to representing biological sequences …
A deep learning model for DNA enhancer prediction based on nucleotide position aware feature encoding
W Hu, Y Li, Y Wu, L Guan, M Li - Iscience, 2024 - cell.com
Enhancers, genomic DNA elements, regulate neighboring gene expression crucial for
biological processes like cell differentiation and stress response. However, current machine …
biological processes like cell differentiation and stress response. However, current machine …
Ienhancer-Flow: Integrating Transformer-Based Sequence Learning with DNA Shape Insights for Robust Enhancer Prediction
H Liu, H Luo, L Luo - Available at SSRN 5074657 - papers.ssrn.com
AbstractObjective: Enhancers are critical non-coding regulatory elements, but their
prediction remains challenging due to their variability and the absence of clear sequence …
prediction remains challenging due to their variability and the absence of clear sequence …