Article

Predicting dynamic cellular protein-RNA interactions using deep learning and <i>in vivo</i> RNA structure

2020-05-07

Abstract excerpt

Interactions with RNA-binding proteins (RBPs) are crucial for RNA regulation and function. While both RNA sequence and structure are critical determinants, RNA structure is dependent on cellular environment and especially important in regulating dynamic RBP bindings across various conditions. However, how distinct it contributes to RBP binding in vivo remains poorly understood. To address this issue, we obtained...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 75b50c43-091f-5c03-9d32-c81ba26cd09b
DOI: 10.1101/2020.05.05.078774

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting dynamic cellular protein-RNA interactions using deep learning and <i>in vivo</i> RNA structureDOI 10.1101/2020.05.05.078774Read

<i>In-silico</i> modeling and interpretation of RBP binding disentangle m <sup>6</sup> A-RBP interactionSemantic proximity Read

Bridging sequence-structure motifs and genetic variants for genome-wide dynamic RNA-protein interaction profiling.Semantic proximity Read

DeepCLIP: predicting the effect of mutations on protein-RNA binding with deep learning.Semantic proximity Read

DeepCLIP: Predicting the effect of mutations on protein-RNA binding with Deep LearningSemantic proximity Read

Comprehensive RNA-binding protein analyses and deep learning uncover genetic constraints and disease associations in protein-RNA interfaces.Semantic proximity Read

Pan-cell-type prediction of splicing patterns from sequence and splicing factor expressionSemantic proximity Read

HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequenceSemantic proximity Read

RMDisease V2.0: an updated database of genetic variants that affect RNA modifications with disease and trait implication.Semantic proximity Read

Genome-Wide Mapping of RNA-Protein Associations via SequencingSemantic proximity Read

Deep learning predicts non-coding RNA functions from only raw sequence dataSemantic proximity Read

Diverse Database and Machine Learning Model to Narrow the Generalization Gap in RNA Structure PredictionSemantic proximity Read

RNA <i>in situ</i> conformation sequencing reveals novel long-range RNA structures with impact on splicingSemantic proximity Read