ReviewBriefings in functional genomics2015
Biochemical and bioinformatic methods for elucidating the role of RNA-protein interactions in posttranscriptional regulation.
Review in Briefings in functional genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- A comparative analysis of machine learning classifiers for predicting protein-binding nucleotides in RNA sequences.Computational and structural biotechnology journal · 2022Article
- Transcriptome-wide analysis uncovers the targets of the RNA-binding protein MSI2 and effects of MSI2's RNA-binding activity on IL-6 signaling.The Journal of biological chemistry · 2018Article
- A network-based analysis of colon cancer splicing changes reveals a tumorigenesis-favoring regulatory pathway emanating from ELK1.Genome research · 2016Article
- Revealing protein-lncRNA interaction.Briefings in bioinformatics · 2016Review
- Article
- Prediction of RNA- and DNA-Binding Proteins Using Various Machine Learning Classifiers.Avicenna journal of medical biotechnologyArticle
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our understanding of transcriptional gene regulation has dramatically increased over the past decades, and many regulators of gene expression, such as transcription factors, have been analyzed extensively. Additionally, in recent years, deeper insights into the physiological roles of RNA have been obtained. More precisely, splicing, polyadenylation, various modifications, localization and the translation of messenger RNAs (mRNAs) are regulated by their interaction with RNA-binding proteins (RBPs). New technologies now enable the analysis of this regulation at different levels. A technique known as ultraviolet (UV) cross-linking and immunoprecipitation (CLIP) allows us to determine physical protein-RNA interactions on a genome-wide scale. UV cross-linking introduces covalent bonds between interacting RBPs and RNAs. In combination with immunoprecipitation and deep sequencing techniques, tens of millions of short reads (representing bound RNAs by an RBP of interest) are generated and are used to characterize the regulatory network mediated by an RBP. Other methods, such as mass spectrometry, can also be used for characterization of cross-linked RBPs and RNAs instead of CLIP methods. In this review, we discuss experimental and computational methods for the generation and analysis of CLIP data. The computational methods include short-read alignment, annotation and RNA-binding motif discovery. We describe the challenges of analyzing CLIP data and indicate areas where improvements are needed.
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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.