LncRNA–protein interaction prediction with reweighted feature selection [PDF]
BMC Bioinformatics, 2023 LncRNA–protein interactions are ubiquitous in organisms and play a crucial role in a variety of biological processes and complex diseases. Many computational methods have been reported for lncRNA–protein interaction prediction.
Guohao Lv +8 more
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Predicting lncRNA–Protein Interaction With Weighted Graph-Regularized Matrix Factorization [PDF]
Frontiers in Genetics, 2021 Long non-coding RNAs (lncRNAs) are widely concerned because of their close associations with many key biological activities. Though precise functions of most lncRNAs are unknown, research works show that lncRNAs usually exert biological function by ...
Xibo Sun +7 more
doaj +5 more sources
LPInsider: a webserver for lncRNA–protein interaction extraction from the literature [PDF]
BMC Bioinformatics, 2022 Background Long non-coding RNA (LncRNA) plays important roles in physiological and pathological processes. Identifying LncRNA–protein interactions (LPIs) is essential to understand the molecular mechanism and infer the functions of lncRNAs.
Ying Li +6 more
doaj +4 more sources
Protocol for detecting lncRNA-protein interaction in vivo using the yeast three-hybrid assay [PDF]
STAR ProtocolsSummary: Analyses of long non-coding RNA (lncRNA)-protein interactions provide key clues for understanding the molecular basis of lncRNA-modulated biological processes. Here, we detail a yeast three-hybrid assay to identify the lncRNA-interacting protein.
Jingjing Cai +5 more
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Prediction of lncRNA-protein interactions using HeteSim scores based on heterogeneous networks
Scientific Reports, 2017 Massive studies have indicated that long non-coding RNAs (lncRNAs) are critical for the regulation of cellular biological processes by binding with RNA-related proteins.
Yun Xiao, Jingpu Zhang, Lei Deng
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Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network. [PDF]
BMC Bioinformatics, 2021 Abstract Background Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA–protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging.
Li Y +5 more
europepmc +5 more sources
LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification [PDF]
BioData Mining, 2021 Background Long noncoding RNAs (lncRNAs) have dense linkages with various biological processes. Identifying interacting lncRNA-protein pairs contributes to understand the functions and mechanisms of lncRNAs. Wet experiments are costly and time-consuming.
Lihong Peng +4 more
doaj +2 more sources
PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions [PDF]
BMC Bioinformatics, 2021 Background Plant long non-coding RNAs (lncRNAs) play vital roles in many biological processes mainly through interactions with RNA-binding protein (RBP).
Haoran Zhou +3 more
doaj +3 more sources
LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization. [PDF]
Oncotarget, 2017 LncRNA-protein interactions play important roles in many important cellular processes including signaling, transcriptional regulation, and even the generation and progression of complex diseases. However, experimental methods for determining proteins bound by a specific lncRNA remain expensive, difficult and time-consuming, and only a few theoretical ...
Liu H +6 more
europepmc +4 more sources
The Interaction of lncRNA-HEIH and lncRNA-HULC with HBXIP in Hepatitis B Patients
Gastroenterology Research and Practice, 2018 Hepatitis B virus (HBV) infection is a major risk factor for the development of hepatic cirrhosis (HC) and hepatocellular carcinoma (HCC), which are associated with very high morbidity and mortality rates worldwide.
Lingjuan Ruan +7 more
doaj +2 more sources