Evidence map›Paper›PMID 26976934›Full record

ReviewMolecular biology of the cell2016

Old knowledge and new technologies allow rapid development of model organisms.

Charles E Cook, Janet Chenevert, Tomas A Larsson, Detlev Arendt, Evelyn Houliston, Péter Lénárt

Abstract readReview
In one paragraph

Review in Molecular biology of the cell, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Deep homology in the age of next-generation sequencing.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017
    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

6 authors.

Charles E CookEuropean Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.
Janet ChenevertSorbonne Universités, UPMC Univ Paris 06, CNRS, Laboratoire de Biologie du Développement de Villefranche-sur-mer, 06230 Villefranche-sur-mer, France.
Tomas A LarssonDevelopmental Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Detlev ArendtDevelopmental Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
Evelyn HoulistonSorbonne Universités, UPMC Univ Paris 06, CNRS, Laboratoire de Biologie du Développement de Villefranche-sur-mer, 06230 Villefranche-sur-mer, France.
Péter LénártCell Biology and Biophysics Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany lenart@embl.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Until recently the set of "model" species used commonly for cell biology was limited to a small number of well-understood organisms, and developing a new model was prohibitively expensive or time-consuming. With the current rapid advances in technology, in particular low-cost high-throughput sequencing, it is now possible to develop molecular resources fairly rapidly. Wider sampling of biological diversity can only accelerate progress in addressing cellular mechanisms and shed light on how they are adapted to varied physiological contexts. Here we illustrate how historical knowledge and new technologies can reveal the potential of nonconventional organisms, and we suggest guidelines for selecting new experimental models. We also present examples of nonstandard marine metazoan model species that have made important contributions to our understanding of biological processes.

Indexed as

Cell BiologyModels, AnimalAnimals

Identifiers

PMID26976934
PMCPMC4791132

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.