LPIH2V: LncRNA-protein interactions prediction using HIN2Vec based on heterogeneous networks model
Frontiers in Genetics, 2023 LncRNA-protein interaction plays an important role in the development and treatment of many human diseases. As the experimental approaches to determine lncRNA–protein interactions are expensive and time-consuming, considering that there are few ...
Meng-Meng Wei +8 more
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LncPTPred: predicting lncRNA-protein interaction based on crosslinking and immunoprecipitation (CLIP-Seq) data. [PDF]
Brief BioinformAbstract Long noncoding RNA (lncRNA)–protein Interaction (LPI) across diverse biological systems, directly and indirectly, regulates various cellular processes. Experimental assays to recognize the protein binding partners of lncRNAs are highly time-consuming and expensive.
Das G, Das T, Ghosh Z.
europepmc +6 more sources
Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks
Frontiers in Genetics, 2023 Background: Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes. Investigation of the lncRNA-protein interaction contributes to discovering the undetected molecular functions of lncRNAs.
Yuzhou Ma +3 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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Probing lncRNA–Protein Interactions: Data Repositories, Models, and Algorithms
Frontiers in Genetics, 2020 Identifying lncRNA-protein interactions (LPIs) is vital to understanding various key biological processes. Wet experiments found a few LPIs, but experimental methods are costly and time-consuming. Therefore, computational methods are increasingly exploited to capture LPI candidates.
Lihong Peng +2 more
exaly +4 more sources
IEEE Access, 2019 Long non-coding RNA, also known as lncRNA, is a series of single-stranded polynucleotides (no less than 200 nucleotides each), consisting of non-protein coding transcripts.
Cong Shen +4 more
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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
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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.
Yushi Luan +2 more
exaly +3 more sources
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 +6 more sources
Protocol for detecting lncRNA-protein interactions in vitro by tRSA RNA pull-down assay
STAR ProtocolsSummary: Long non-coding RNAs (lncRNAs) work together with diverse RNA-binding proteins (RBPs) to fulfill key regulations in important cellular functions.
Liyun Jiang +4 more
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