Evidence map›Paper›PMID 30232369›Full record

ReviewNature reviews. Genetics2018

Computational tools to unmask transposable elements.

Patricia Goerner-Potvin, Guillaume Bourque

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers.

0numbers the graph read from it
0cells of the map it votes in
122citing papers in PubMed
43.9field-weighted citation impact, top 1% 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

122 citing papers in PubMed, 249 citations in OpenAlex.

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  17. Evolution letters · 2025
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62 more citing papers are in PubMed but not listed here.

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

2 authors at 2 institutions in 1 country.

Patricia Goerner-PotvinDepartment of Human Genetics, McGill University, Montréal, Canada.
Guillaume BourqueDepartment of Human Genetics, McGill University, Montréal, Canada. guil.bourque@mcgill.ca.ORCID http://orcid.org/0000-0002-3933-9656
McGill Genome Centre · CAMcGill University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A substantial proportion of the genome of many species is derived from transposable elements (TEs). Moreover, through various self-copying mechanisms, TEs continue to proliferate in the genomes of most species. TEs have contributed numerous regulatory, transcript and protein innovations and have also been linked to disease. However, notwithstanding their demonstrated impact, many genomic studies still exclude them because their repetitive nature results in various analytical complexities. Fortunately, a growing array of methods and software tools are being developed to cater for them. This Review presents a summary of computational resources for TEs and highlights some of the challenges and remaining gaps to perform comprehensive genomic analyses that do not simply 'mask' repeats.

Indexed as

Computational BiologyDNA Transposable ElementsEvolution, MolecularGenomicsSoftwareDNA Transposable Elements

Identifiers

PMID30232369
OpenAlexW2892332606

What OpenQuestion holds

Textmetadata
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.