Evidence map›Paper›PMID 28248922›Full record

ArticleScientific data2017

Knocking down the obstacles to functional genomics data sharing.

Kaylene J Simpson, Jennifer A Smith

Abstract readComment
In one paragraph

Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Kaylene J SimpsonVictorian Centre for Functional Genomics, Peter MacCallum Cancer Centre, Melbourne 3000, Australia.
Jennifer A SmithICCB-Longwood Screening Facility, Harvard Medical School, Boston, Massachusetts 02115, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This week, Scientific Data published a collection of eight papers that describe datasets from high-throughput functional genomics screens, primarily utilizing RNA interference (RNAi). The publications explore host-pathogen dependencies, innate immune response, disease pathways, and cell morphology and motility at the genome-level. All data, including raw images from the high content screens, are publically available in PubChem BioAssay, figshare, Harvard Dataverse or the Image Data Resource (IDR). Detailed data descriptors enable use of these data for analysis algorithm design, machine learning, data comparisons, as well as generating new scientific hypotheses.

Indexed as

Information DisseminationRNA InterferenceGenomicsHumans

Identifiers

PMID28248922
PMCPMC5332007

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.