AIMC Topic: RNA-Binding Proteins

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PST-PRNA: prediction of RNA-binding sites using protein surface topography and deep learning.

Bioinformatics (Oxford, England) Apr 12, 2022
MOTIVATION: Protein-RNA interactions play essential roles in many biological processes, including pre-mRNA processing, post-transcriptional gene regulation and RNA degradation. Accurate identification of binding sites on RNA-binding proteins (RBPs) i...
Deep Learning Membrane Proteins RNA Binding Sites Protein Binding Computational Biology RNA-Binding Proteins
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Protein-RNA interaction prediction with deep learning: structure matters.

Briefings in bioinformatics Jan 17, 2022
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 lac...
Algorithms Deep Learning Computational Biology Binding Sites RNA-Binding Proteins RNA Protein Conformation
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DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.

Briefings in bioinformatics Jan 17, 2022
Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported by computational predictors, but to date, only one tool that predicts...
Humans Neural Networks, Computer DNA DNA-Binding Proteins RNA Intrinsically Disordered Proteins Nucleic Acids Computational Biology Deep Learning RNA-Binding Proteins Protein Binding Proteome
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EDCNN: identification of genome-wide RNA-binding proteins using evolutionary deep convolutional neural network.

Bioinformatics (Oxford, England) Jan 12, 2022
MOTIVATION: RNA-binding proteins (RBPs) are a group of proteins associated with RNA regulation and metabolism, and play an essential role in mediating the maturation, transport, localization and translation of RNA. Recently, Genome-wide RNA-binding e...
RNA-Binding Proteins RNA Software Algorithms Neural Networks, Computer
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Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Briefings in bioinformatics Nov 5, 2021
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is ...
Binding Sites RNA, Circular ROC Curve Computational Biology RNA-Binding Proteins Databases, Genetic Base Sequence Algorithms Reproducibility of Results Deep Learning
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RNAProt: an efficient and feature-rich RNA binding protein binding site predictor.

GigaScience Aug 18, 2021
BACKGROUND: Cross-linking and immunoprecipitation followed by next-generation sequencing (CLIP-seq) is the state-of-the-art technique used to experimentally determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). However, it relies...
RNA Binding Sites Neural Networks, Computer Protein Binding RNA-Binding Proteins
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GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues.

Nucleic acids research May 21, 2021
Knowledge of the interactions between proteins and nucleic acids is the basis of understanding various biological activities and designing new drugs. How to accurately identify the nucleic-acid-binding residues remains a challenging task. In this pap...
Neural Networks, Computer Software Protein Binding Protein Conformation DNA-Binding Proteins RNA-Binding Proteins RNA Binding Sites DNA
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RNA-binding protein recognition based on multi-view deep feature and multi-label learning.

Briefings in bioinformatics May 20, 2021
RNA-binding protein (RBP) is a class of proteins that bind to and accompany RNAs in regulating biological processes. An RBP may have multiple target RNAs, and its aberrant expression can cause multiple diseases. Methods have been designed to predict ...
Machine Learning Computational Biology RNA-Binding Proteins Neural Networks, Computer
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Modeling multi-species RNA modification through multi-task curriculum learning.

Nucleic acids research Apr 19, 2021
N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, ...
Datasets as Topic Gene Expression Regulation Adenosine Humans Databases, Genetic Transcriptome Machine Learning RNA RNA-Binding Proteins Software Sequence Analysis, RNA Animals
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DeepCLIP: predicting the effect of mutations on protein-RNA binding with deep learning.

Nucleic acids research Jul 27, 2020
Nucleotide variants can cause functional changes by altering protein-RNA binding in various ways that are not easy to predict. This can affect processes such as splicing, nuclear shuttling, and stability of the transcript. Therefore, correct modeling...
Binding Sites Nucleotide Motifs Base Sequence Nucleic Acid Conformation Mice RNA-Binding Proteins Animals Humans Computational Biology Mutation Computer Simulation Deep Learning RNA Protein Binding
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