ArticlePloS one2014
A model-based approach to identify binding sites in CLIP-Seq data.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Associating cancer-related RNA structure disrupting SNPs in LincRNAs to function.BMC genomics · 2025Article
- Epitranscriptomic sculpting: the role of mMedical oncology (Northwood, London, England) · 2025Review
- POSTAR3: an updated platform for exploring post-transcriptional regulation coordinated by RNA-binding proteins.Nucleic acids research · 2022Article
- Introduction to Bioinformatics Resources for Post-transcriptional Regulation of Gene Expression.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Advances in mRNA 5-methylcytosine modifications: Detection, effectors, biological functions, and clinical relevance.Molecular therapy. Nucleic acids · 2021Review
- Large-scale analysis of the position-dependent binding and regulation of human RNA binding proteins.Quantitative biology (Beijing, China) · 2020Article
- PRAS: Predicting functional targets of RNA binding proteins based on CLIP-seq peaks.PLoS computational biology · 2019Article
- Beyond CLIP: advances and opportunities to measure RBP-RNA and RNA-RNA interactions.Nucleic acids research · 2019Review
- Practical considerations on performing and analyzing CLIP-seq experiments to identify transcriptomic-wide RNA-protein interactions.Methods (San Diego, Calif.) · 2019Review
- CLIPick: a sensitive peak caller for expression-based deconvolution of HITS-CLIP signals.Nucleic acids research · 2018Article
- Recent computational developments on CLIP-seq data analysis and microRNA targeting implications.Briefings in bioinformatics · 2018Review
- Mapping transcriptome-wide protein-RNA interactions to elucidate RNA regulatory programs.Quantitative biology (Beijing, China) · 2018Article
- Bioinformatic tools for analysis of CLIP ribonucleoprotein data.Wiley interdisciplinary reviews. RNA · 2017Review
- From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data.Nucleic acids research · 2017Article
- CLIPSeqTools--a novel bioinformatics CLIP-seq analysis suite.RNA (New York, N.Y.) · 2016Article
- Revealing protein-lncRNA interaction.Briefings in bioinformatics · 2016Review
- Design and bioinformatics analysis of genome-wide CLIP experiments.Nucleic acids research · 2015Review
- Intramolecular circularization increases efficiency of RNA sequencing and enables CLIP-Seq of nuclear RNA from human cells.Nucleic acids research · 2015Article
- Assessing Computational Steps for CLIP-Seq Data Analysis.BioMed research international · 2015Article
- Computational challenges, tools, and resources for analyzing co- and post-transcriptional events in high throughput.Wiley interdisciplinary reviews. RNAReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip) to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets. In the HITS-CLIP dataset, the signal/noise ratios of miRNA seed motif enrichment produced by the MiClip approach are between 17% and 301% higher than those by the ad hoc method for the top 10 most enriched miRNAs. In the PAR-CLIP dataset, the MiClip approach can identify ∼50% more validated binding targets than the original ad hoc method and two recently published methods. To facilitate the application of the algorithm, we have released an R package, MiClip (http://cran.r-project.org/web/packages/MiClip/index.html), and a public web-based graphical user interface software (http://galaxy.qbrc.org/tool_runner?tool_id=mi_clip) for customized analysis.
Indexed as
Identifiers
What OpenQuestion holds
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.