Evidence map›Paper›PMID 28575075›Full record

ArticlePloS one2017

SeqEnrich: A tool to predict transcription factor networks from co-expressed Arabidopsis and Brassica napus gene sets.

Michael G Becker, Philip L Walker, Nadège C Pulgar-Vidal, Mark F Belmonte

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Michael G BeckerDepartment of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Philip L WalkerDepartment of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
Nadège C Pulgar-VidalDepartment of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada.
Mark F BelmonteDepartment of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.ORCID http://orcid.org/0000-0002-3141-3903

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription factors and their associated DNA binding sites are key regulatory elements of cellular differentiation, development, and environmental response. New tools that predict transcriptional regulation of biological processes are valuable to researchers studying both model and emerging-model plant systems. SeqEnrich predicts transcription factor networks from co-expressed Arabidopsis or Brassica napus gene sets. The networks produced by SeqEnrich are supported by existing literature and predicted transcription factor-DNA interactions that can be functionally validated at the laboratory bench. The program functions with gene sets of varying sizes and derived from diverse tissues and environmental treatments. SeqEnrich presents as a powerful predictive framework for the analysis of Arabidopsis and Brassica napus co-expression data, and is designed so that researchers at all levels can easily access and interpret predicted transcriptional circuits. The program outperformed its ancestral program ChipEnrich, and produced detailed transcription factor networks from Arabidopsis and Brassica napus gene expression data. The SeqEnrich program is ideal for generating new hypotheses and distilling biological information from large-scale expression data.

Indexed as

Gene Expression Regulation, PlantArabidopsisArabidopsis ProteinsBrassica napusDNA, PlantGenes, PlantGenomicsPlant ProteinsProtein Interaction MapsSoftwareTranscriptional ActivationTranscription FactorsArabidopsis ProteinsDNA, PlantPlant ProteinsTranscription Factors

Identifiers

PMID28575075
PMCPMC5456048

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.