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Multi-feature fusion for deep learning to predict plant lncRNA-protein interaction

Genomics, 2020
Long non-coding RNAs (lncRNAs) play key roles in regulating cellular biological processes through diverse molecular mechanisms including binding to RNA binding proteins. The majority of plant lncRNAs are functionally uncharacterized, thus, accurate prediction of plant lncRNA-protein interaction is imperative for subsequent functional studies.
Jael Sanyanda Wekesa, Jun Meng, Yushi Luan   +2 more
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Identification of lncRNA–Protein Interactions by CLIP and RNA Pull-Down Assays

2021
The emerging data indicates that long noncoding RNAs (lncRNAs) are involved in fundamental biological processes, and their deregulation may lead to oncogenesis and other diseases. LncRNA fulfil its biological functions at least in part by interacting with distinctive proteins.
Kunming, Zhao, Xingwen, Wang, Ying, Hu
openaire   +2 more sources

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.
Jael Sanyanda Wekesa, Jun Meng, Yushi Luan   +2 more
openaire   +2 more sources

LPLSG: Prediction of lncRNA-protein Interaction Based on Local Network Structure

Current Bioinformatics, 2023
Background: 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. Because the interaction between RNA and protein is tissue-specific and condition-specific, it is time-consuming and expensive to predict the interaction ...
Wei Wang, Yongqing Wang, Bin Sun, Shihao Liang, Dong Liu, Hongjun Zhang, Xianfang Wang   +6 more
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Predicting lncRNA-protein Interactions by Machine Learning Methods: A Review

Current Bioinformatics, 2021
In this work, a review of predicting lncRNA-protein interactions by bioinformatics methods is provided with a focus on machine learning. Firstly, a computational framework for predicting lncRNA-protein interactions is presented. Then, the currently available data resources for the predictions have been listed. The existing methods will be reviewed by
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A text feature-based approach for literature mining of lncRNA–protein interactions

Neurocomputing, 2016
Long non-coding RNAs (lncRNAs) play important roles in regulating transcriptional and post-transcriptional levels. Currently, Knowledge of lncRNA and protein interactions (LPIs) is crucial for biomedical researches that are related to lncRNA. Many freshly discovered LPIs are stored in biomedical literature.
Ao Li 0001, Qiguang Zang, Dongdong Sun, Minghui Wang   +3 more
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Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022
The identification of lncRNA-protein interactions (LPIs) is important to understand the biological functions and molecular mechanisms of lncRNAs. However, most computational models are evaluated on a unique dataset, thereby resulting in prediction bias.
Lihong Peng, Chang Wang, Xiongfei Tian, Liqian Zhou, Keqin Li 0001   +4 more
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Cross-domain contrastive graph neural network for lncRNA–protein interaction prediction

Knowledge-Based Systems
Zhenfeng Zhu, Miaomiao Sun, Hui Li
exaly   +2 more sources

Diverging RNPs: Toward Understanding lncRNA-Protein Interactions and Functions

2019
RNA-protein interactions are essential to a variety of biological processes. The realization that mammalian genomes are pervasively transcribed brought a tidal wave of tens of thousands of newly identified long noncoding RNAs (lncRNAs) and raised questions about their purpose in cells. The vast majority of lncRNAs have yet to be studied, and it remains
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Structure-Based Prediction of lncRNA–Protein Interactions by Deep Learning

The interactions between long noncoding RNA (lncRNA) and protein play crucial roles in various biological processes. Computational methods are essential for predicting lncRNA-protein interactions and deciphering their mechanisms. In this chapter, we aim to introduce the fundamental framework for predicting lncRNA-protein interactions based on three ...
Pengpai, Li, Zhi-Ping, Liu
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