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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 ...
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Prediction of LncRNA-protein Interactions Using Auto-Encoder, SE-ResNet Models and Transfer Learning

MicroRNA
Background: Long non-coding RNA (lncRNA) plays a crucial role in various biolog-ical processes, and mutations or imbalances of lncRNAs can lead to several diseases, including cancer, Prader-Willi syndrome, autism, Alzheimer's disease, cartilage-hair hypoplasia, and hear-ing loss.
Jiang Huiwen, Song Kai
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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
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Mechanisms, regulation and functions of the unfolded protein response

Nature Reviews Molecular Cell Biology, 2020
Claudio Hetz   +2 more
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Biomolecular condensates at the nexus of cellular stress, protein aggregation disease and ageing

Nature Reviews Molecular Cell Biology, 2021
Simon Alberti, Anthony A Hyman
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The mechanisms of integral membrane protein biogenesis

Nature Reviews Molecular Cell Biology, 2021
Ramanujan Shankar Hegde, Robert J Keenan
exaly  

Derivatization with fatty acids in peptide and protein drug discovery

Nature Reviews Drug Discovery, 2022
Peter Kurtzhals   +2 more
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Functions and mechanisms of non-histone protein acetylation

Nature Reviews Molecular Cell Biology, 2018
Takeo Narita, Chunaram Choudhary
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Advances in protein structure prediction and design

Nature Reviews Molecular Cell Biology, 2019
Brian Kuhlman, Philip Bradley
exaly  

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