Evidence map›Paper›PMID 41278533›Full record

ArticleNAR genomics and bioinformatics2025

LncPlankton: a comprehensive database of candidate lncRNAs from marine microbial eukaryotes.

Ahmed Debit, Pierre Vincens, Chris Bowler, Helena Cruz de Carvalho

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ahmed DebitInstitut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, Paris 75005, France.ORCID https://orcid.org/0000-0002-2662-0772
Pierre VincensInstitut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, Paris 75005, France.
Chris BowlerInstitut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, Paris 75005, France.ORCID https://orcid.org/0000-0003-3835-6187
Helena Cruz de CarvalhoInstitut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, Paris 75005, France.ORCID https://orcid.org/0000-0002-2223-3556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Historically neglected or considered to be mere transcriptional noise, long non-coding RNAs (lncRNAs) are now emerging as central, regulatory molecules in a multitude of eukaryotic species, from animals to plants to fungi. Yet, our knowledge about the occurrence of these molecules in the marine environment is still elusive. To help fill this knowledge gap, we have developed LncPlankton, a comprehensive database of candidate marine lncRNAs. By integrating the predictions derived from 10 distinctive coding potential prediction tools in a majority voting setting, we have identified over 2M potential lncRNAs distributed across 414 marine plankton species from over nine different phyla. A user-friendly, open-access web interface of the database has been implemented to facilitate exploration (https://www.lncplankton.bio.ens.psl.eu/). We believe LncPlankton will serve as a rich resource for studies of lncRNAs, which will contribute to small- and large-scale analyses in a wide range of marine plankton species and allow comparative studies between them and well beyond the marine environment.

Indexed as

Aquatic OrganismsDatabases, GeneticDatabases, Nucleic AcidEukaryotaRNA, Long NoncodingPlanktonRNA, Long Noncoding

Identifiers

PMID41278533
PMCPMC12634410

What OpenQuestion holds

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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.