Evidence map›Paper›PMID 29844966›Full record

ArticlePeerJ2018

Finding novel relationships with integrated gene-gene association network analysis of

Sanna M Kreula, Suwisa Kaewphan, Filip Ginter, Patrik R Jones

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2018. 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
0.2field-weighted citation impact, top 51% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

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 at 2 institutions in 2 countries.

Sanna M KreulaDepartment of Biochemistry, University of Turku, Turku, Finland.
Suwisa KaewphanUniversity of Turku Graduate School, University of Turku, Turku, Finland.
Filip GinterDepartment of Future Technologies, University of Turku, Turku, Finland.
Patrik R JonesDepartment of Life Sciences, Imperial College London, London, United Kingdom.
University of Turku · FIImperial College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for

Indexed as

CyanobacteriaMetabolismNetwork analysisSynechocystis sp. PCC 6803Systems biologyText-mining

Identifiers

PMID29844966
PMCPMC5970561
OpenAlexW2778105755

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.