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LncRNA Rmst-driven DNMT3A mRNA stabilization through HuR: implications for neuropathic pain therapy. [PDF]

Eur J Med Res
Zhang S, Jiang P, Li Y, Tu Y.
europepmc   +1 more source

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LPLSG: Prediction of lncRNA-protein interaction based on local network structure

Current Bioinformatics, 2023
The interaction between RNA and protein plays an important role in life activities. Long ncRNAs (lncRNAs) are large non-coding RNAs, and have received extensive attention in recent years.
Wei Wang, Yongqing Wang, Bin Sun, Shi Liang, Dong Liu, Hongjun Zhang, Xianfang Wang   +6 more
semanticscholar   +2 more sources

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

2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021
Long non-coding RNAs(lncRNAs) play an important role in various biological processes. lncRNAs usually perform their molecular functions by interacting with proteins.
Chengcai Jin, Zhuangwei Shi, Han Zhang, Yanbin Yin   +3 more
semanticscholar   +2 more sources

A Deep Neural Network Model with Attribute Network Representation for lncRNA-Protein Interaction Prediction

Current Bioinformatics, 2023
LncRNA is not only involved in the regulation of the biological functions of protein-coding genes but its dysfunction is also associated with the occurrence and progression of various diseases.
Mengchao Wei, Changqing Yu, Liping Li, Zhuhong You, Lei Wang   +4 more
semanticscholar   +1 more source

iEssLnc: quantitative estimation of lncRNA gene essentialities with meta-path-guided random walks on the lncRNA-protein interaction network

Briefings Bioinform., 2023
Gene essentiality is defined as the extent to which a gene is required for the survival and reproductive success of a living system. It can vary between genetic backgrounds and environments. Essential protein coding genes have been well studied. However,
Ying-ying Zhang, De-Min Liang, Pu-Feng Du   +2 more
semanticscholar   +1 more source

A deep learning model for plant lncRNA-protein interaction prediction with graph attention

Molecular Genetics and Genomics, 2020
Long non-coding RNAs (lncRNAs) play a broad spectrum of distinctive regulatory roles through interactions with proteins. However, only a few plant lncRNAs have been experimentally characterized. We propose GPLPI, a graph representation learning method, to predict plant lncRNA-protein interaction (LPI) from sequence and structural information.
J. Wekesa, Jun Meng, Yushi Luan
semanticscholar   +3 more sources

Computational Prediction of lncRNA-Protein Interactions using Machine learning

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021
Long non-coding RNAs have generated much scientific interest because of their functional significance in regulating various biological processes and also their dysfunction has been implicated in disease progression. LncRNAs usually bind with proteins to perform their function.
Muhammad, Mushtaq, Hammad, Naveed, Zoya, Khalid   +2 more
openaire   +2 more sources