2021
DOI: 10.1093/bib/bbab540
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Protein–RNA interaction prediction with deep learning: structure matters

Abstract: Protein–RNA interactions are of vital importance to a variety of cellular activities. Both experimental and computational techniques have been developed to study the interactions. Because of the limitation of the previous database, especially the lack of protein structure data, most of the existing computational methods rely heavily on the sequence data, with only a small portion of the methods utilizing the structural information. Recently, AlphaFold has revolutionized the entire protein and biology field. Fo… Show more

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Cited by 50 publications
(30 citation statements)
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References 152 publications
(186 reference statements)
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“…RNA-FM carries secondary structure information for RNA-protein interaction modelling. Protein-RNA interactions are of vital importance in various cellular activities, including cell-signalling, post-transcriptional regulations, and protein synthesis [59]. We reproduce PrismNet [36], which includes in vivo RNA secondary structure profiles for RNA-protein interaction prediction.…”
Section: Featuresmentioning
confidence: 99%
See 1 more Smart Citation
“…RNA-FM carries secondary structure information for RNA-protein interaction modelling. Protein-RNA interactions are of vital importance in various cellular activities, including cell-signalling, post-transcriptional regulations, and protein synthesis [59]. We reproduce PrismNet [36], which includes in vivo RNA secondary structure profiles for RNA-protein interaction prediction.…”
Section: Featuresmentioning
confidence: 99%
“…Protein-RNA interaction. Protein-RNA interactions play important roles in a plenty of activities, such as cell-signaling, post-transcriptional regulations and protein synthesis [59]. Therefore, considering the importance of protein-RNA interactions in RNA function, we evaluate how well RNA-FM mine ncRNA function information by predicting RNA binding proteins corresponding to RNAs.…”
Section: Downstream Training Strategiesmentioning
confidence: 99%
“…RNA-FM carries secondary structure information for RNA-protein interaction modeling. Protein-RNA interactions are of vital importance in various cellular activities, including cell-signaling, post-transcriptional regulations and protein synthesis [56]. We reproduce PrismNet [36], which includes in vivo RNA secondary structure profiles for RNA-protein interaction prediction.…”
Section: )))))))))))))mentioning
confidence: 99%
“…Protein-RNA interaction. Protein-RNA interactions play important roles in a plenty of activities, such as cell-signaling, post-transcriptional regulations and protein synthesis [56]. Therefore, considering the importance of protein-RNA interactions in RNA function, we evaluate how well RNA-FM mine ncRNA function information by predicting RNA binding proteins corresponding to RNAs.…”
Section: Downstream Training Strategiesmentioning
confidence: 99%
“…Recently, deep learning has demonstrated high prediction accuracy in computer vision tasks [25] as well as in computational biology [26, 27, 28]. A simple neural network can obtain very complex underlying features, which is especially suitable for large-scale data sets and sparse dimension cases.…”
Section: Introductionmentioning
confidence: 99%