Evidence map›Paper›PMID 37169395›Full record

ArticleRNA (New York, N.Y.)2023

Comparison of TRIBE and STAMP for identifying targets of RNA binding proteins in human and

Katharine C Abruzzi, Corrie Ratner, Michael Rosbash

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Challenges to mapping and defining mRNA (New York, N.Y.) · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Identification of RNA-Binding Protein Targets with HyperTRIBE inInternational journal of molecular sciences · 2023
    Article
  8. Review
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

3 authors at 2 institutions in 1 country.

Katharine C Abruzzi *Howard Hughes Medical Institute, Brandeis University, Waltham, Massachusetts 02454, USA.ORCID 0000-0003-3949-3095
Corrie Ratner *Howard Hughes Medical Institute, Brandeis University, Waltham, Massachusetts 02454, USA.
Michael RosbashHoward Hughes Medical Institute, Brandeis University, Waltham, Massachusetts 02454, USA rosbash@brandeis.edu.
Howard Hughes Medical Institute · USBrandeis University · US

Funding

A new tool for the cell-specific identification of RNA binding protein targetsR01DA037721 · NIDA · BRANDEIS UNIVERSITY · PI ROSBASH, MICHAEL · 2013 to 2021
$2.4M
Addressing Protein Synthesis Regulation within Small Numbers of Discrete NeuronsR01NS130670 · NINDS · BRANDEIS UNIVERSITY · PI MICHAEL ROSBASH · 2023 to 2026
$1.6M
Howard Hughes Medical InstituteNIDA NIH HHS R01 DA037721NINDS NIH HHS R01 NS130670
6 · The paper itself

Abstract

RNA binding proteins (RBPs) perform a myriad of functions and are implicated in numerous neurological diseases. To identify the targets of RBPs in small numbers of cells, we developed TRIBE, in which the catalytic domain of the RNA editing enzyme ADAR (ADARcd) is fused to an RBP. When the RBP binds to an mRNA, ADAR catalyzes A to G modifications in the target mRNA that can be easily identified in standard RNA sequencing. In STAMP, the concept is the same except the ADARcd is replaced by the RNA editing enzyme APOBEC. Here we compared TRIBE and STAMP side-by-side in human and

Indexed as

DrosophilaDrosophila ProteinsAnimalsDNA-Binding ProteinsHumansRNA-Binding ProteinsRNA, MessengerDNA-Binding ProteinsDrosophila ProteinsRNA-Binding ProteinsRNA, MessengerADARAPOBECRNA binding proteins

Identifiers

PMID37169395
PMCPMC10351885
OpenAlexW4376128939

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.