Evidence map›Paper›PMID 34694603›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

RBPmap: A Tool for Mapping and Predicting the Binding Sites of RNA-Binding Proteins Considering the Motif Environment.

Inbal Paz, Amir Argoetti, Noa Cohen, Niv Even, Yael Mandel-Gutfreund

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Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  10. p53 activates circASCC3 to repress R-loops and enhance resistance to chemotherapy.Proceedings of the National Academy of Sciences of the United States of America · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Inbal PazFaculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.
Amir ArgoettiFaculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.
Noa CohenFaculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.
Niv EvenFaculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel.
Yael Mandel-GutfreundFaculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel. yaelmg@technion.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA-binding proteins (RBPs) play a key role in post-transcriptional regulation via binding to coding and non-coding RNAs. Recent development in experimental technologies, aimed to identify the targets of RBPs, has significantly broadened our knowledge on protein-RNA interactions. However, for many RBPs in many organisms and cell types, experimental RNA-binding data is not available. In this chapter we describe a computational approach, named RBPmap, available as a web service via http://rbpmap.technion.ac.il/ and as a stand-alone version for download. RBPmap was designed for mapping and predicting the binding sites of any RBP within a nucleic acid sequence, given the availability of an experimentally defined binding motif of the RBP. The algorithm searches for a sub-sequence that significantly matches the RBP motif, considering the clustering propensity of other weak matches within the motif environment. Here, we present different applications of RBPmap for discovering the involvement of RBPs and their targets in a variety of cellular processes, in health and disease states. Finally, we demonstrate the performance of RBPmap in predicting the binding targets of RBPs in large-scale RNA-binding data, reinforcing the strength of the tool in distinguishing cognate binding sites from weak motifs.

Indexed as

AlgorithmsBinding SitesProtein BindingRNARNA-Binding ProteinsSequence Analysis, RNARNARNA-Binding ProteinsBinding site predictionProtein-RNARBPmapRBP motifsRNA-binding proteins (RBPs)

Identifiers

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Registered trials

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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.