ArticleAnnual review of biomedical data science2018
Data Science Issues in Studying Protein-RNA Interactions with CLIP Technologies.
Article in Annual review of biomedical data science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- circMAC: microRNA-conditioned binding-site localization on circular RNA isoforms.Briefings in bioinformatics · 2026Article
- Review
- Bridging technical innovation and computational advances in studies of RNA-protein assemblies.Nature reviews. Genetics · 2026Review
- Signal or noise? RNA-binding proteins and the challenges of binding site assignments.Nucleic acids research · 2026Review
- Structural probing of RNA hairpins quantifies protein occupancy on RNA and links it to function in human cells.bioRxiv : the preprint server for biology · 2026Article
- Evaluation of novel computational methods to identify RNA-binding protein footprints from structural data.RNA (New York, N.Y.) · 2025Article
- Dissecting RNA selectivity mediated by tandem RNA-binding domains.The Journal of biological chemistry · 2025Article
- An atlas of RNA-dependent proteins in cell division reveals the riboregulation of mitotic protein-protein interactions.Nature communications · 2025Article
- DeepFusion: A deep bimodal information fusion network for unraveling protein-RNA interactions using in vivo RNA structures.Computational and structural biotechnology journal · 2024Article
- Widespread 3'UTR capped RNAs derive from G-rich regions in proximity to AGO2 binding sites.BMC biology · 2024Article
- Widespread regulation of the maternal transcriptome by Nanos in Drosophila.PLoS biology · 2024Article
- Understanding species-specific and conserved RNA-protein interactions in vivo and in vitro.Nature communications · 2024Article
- Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.Cell genomics · 2024Article
- Mapping protein-RNA binding in plants with individual-nucleotide-resolution UV cross-linking and immunoprecipitation (plant iCLIP2).Nature protocols · 2024Review
- Article
- Understanding species-specific and conserved RNA-protein interactionsbioRxiv : the preprint server for biology · 2024Article
- Comprehensive mapping of exon junction complex binding sites reveals universal EJC deposition in Drosophila.BMC biology · 2023Article
- Efficient and sensitive profiling of RNA-protein interactions using TLC-CLIP.Nucleic acids research · 2023Article
- Article
- Depletion of the RNA-binding protein PURA triggers changes in posttranscriptional gene regulation and loss of P-bodies.Nucleic acids research · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
An interplay of experimental and computational methods is required to achieve a comprehensive understanding of protein-RNA interactions. UV crosslinking and immunoprecipitation (CLIP) identifies endogenous interactions by sequencing RNA fragments that copurify with a selected RNA-binding protein under stringent conditions. Here we focus on approaches for the analysis of the resulting data and appraise the methods for peak calling, visualization, analysis, and computational modeling of protein-RNA binding sites. We advocate that the sensitivity and specificity of data be assessed in combination for computational quality control. Moreover, we demonstrate the value of analyzing sequence motif enrichment in peaks assigned from CLIP data and of visualizing RNA maps, which examine the positional distribution of peaks around regulated landmarks in transcripts. We use these to assess how variations in CLIP data quality and in different peak calling methods affect the insights into regulatory mechanisms. We conclude by discussing future opportunities for the computational analysis of protein-RNA interaction experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.