Big data and deep learning for RNA biology
H Hwang, H Jeon, N Yeo, D Baek - Experimental & Molecular Medicine, 2024 - nature.com
The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA–miRNA associations
Connections between circular RNAs (circRNAs) and microRNAs (miRNAs) assume a pivotal
position in the onset, evolution, diagnosis and treatment of diseases and tumors. Selecting …
position in the onset, evolution, diagnosis and treatment of diseases and tumors. Selecting …
MSTCRB: Predicting circRNA-RBP interaction by extracting multi-scale features based on transformer and attention mechanism
Y Zhou, H Cui, D Liu, W Wang - International Journal of Biological …, 2024 - Elsevier
CircRNAs play vital roles in biological system mainly through binding RNA-binding protein
(RBP), which is essential for regulating physiological processes in vivo and for identifying …
(RBP), which is essential for regulating physiological processes in vivo and for identifying …
RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding
Circular RNA (circRNA)-microRNA (miRNA) interaction (CMI) plays crucial roles in cellular
regulation, offering promising perspectives for disease diagnosis and therapy. Therefore, it …
regulation, offering promising perspectives for disease diagnosis and therapy. Therefore, it …