Evidence map›Paper›PMID 36272094›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Best Practices to Promote Data Utility and Reuse by the Non-Traditional Model Organism Community.

Garrett S Dunlap, Nicholas D Leigh

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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

2 authors.

Garrett S DunlapBiological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA.
Nicholas D LeighMolecular Medicine and Gene Therapy, Wallenberg Centre for Molecular Medicine, Lund Stem Cell Center, Lund University, Lund, Sweden. nicholas.leigh@med.lu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The dramatic increase in accessibility to sequencing technologies has opened new avenues into studying different processes, cells, and animal models. In the amphibian models used for regeneration research, these new datasets have uncovered a variety of information about what genes define the regenerating limb as well as how genes and cells change over the course of regeneration. The accumulation of data from these studies undoubtedly increases our understanding of regeneration. Throughout these studies, it is important to consider how data can be made most useful not only for the primary study but also for reuse within the scientific community. This chapter will focus on best practices for data collection and handling as well as principles to promote access and reuse of big datasets. However, the deposition and thorough description of data of all sizes generated for a publication (e.g., images, fcs files, etc.) can also be done following this generic workflow. The aim is to lower hurdles for reuse, access, and re-evaluation of data which will in turn increase the utility of these datasets and accelerate scientific progress.

Indexed as

TechnologyData CollectionSequence AnalysisWorkflowBig dataData collectionData repositoriesData reuseData sharingNext-generation sequencing

Identifiers

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.