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Prediction of LncRNA-Protein Interactions Based on Kernel Combinations and Graph Convolutional Networks

IEEE Journal of Biomedical and Health Informatics
The complexes of long non-coding RNAs bound to proteins can be involved in regulating life activities at various stages of organisms. However, in the face of the growing number of lncRNAs and proteins, verifying LncRNA-Protein Interactions (LPI) based on traditional biological experiments is time-consuming and laborious. Therefore, with the improvement
Cong Shen   +4 more
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Prediction of Plant lncRNA-Protein Interactions Using Sequence Information Based on Deep Learning

2019
Plant long non-coding RNA (lncRNA) plays an important role in many biological processes, mainly through its interaction with RNA binding protein (RBP). To understand the function of lncRNA, a basic step is to determine which proteins are interacted with lncRNA. Therefore, RBP can be predicted by computational approaches.
Haoran Zhou   +3 more
openaire   +1 more source

Predicting lncRNA-protein interactions based on graph autoencoders and collaborative training

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021
Chen Jin   +3 more
openaire   +1 more source

Prediction of lncrna-protein interactions based on deep learning model

One main function of long non-coding RNAs (lncRNAs) is to act as a scaffold facilitating multiple proteins to form complexes. Most of available prediction models for protein-RNA interactions, however, were proposed as a binary classifier, which limited on predicting the interaction between the non-coding RNAs and each individual RNA-binding protein ...
openaire   +1 more source

EnANNDeep: An Ensemble-based lncRNA–protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models

Interdisciplinary Sciences, Computational Life Sciences, 2022
Lihong Peng   +2 more
exaly  

Revealing protein–lncRNA interaction

Briefings in Bioinformatics, 2016
Fabrizio FERRÉ   +2 more
exaly  

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