Evidence map›Paper›PMID 21470963›Full record

ArticleNucleic acids research2011

Transcriptional regulation via TF-modifying enzymes: an integrative model-based analysis.

Logan J Everett, Shane T Jensen, Sridhar Hannenhalli

Open access · goldAbstract readValidation Study
In one paragraph

Article in Nucleic acids research, 2011. 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
0.5field-weighted citation impact, top 33% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

3 authors at 3 institutions in 2 countries.

Logan J EverettGenomics and Computational Biology Program, 700 Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104, USA. loganje@mail.med.upenn.edu
Shane T Jensen
Sridhar Hannenhalli
ID Genomics (United States) · USInstitute of Bioinformatics · INPhiladelphia University · US

Funding

Methods for evolutionary analysis of eukaryotic transcriptional regulationR01GM085226 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI HANNENHALLI, SRIDHAR · 2008 to 2011
$1.5M
NHGRI NIH HHS HG000046NIGMS NIH HHS GM085226NIGMS NIH HHS R01 GM085226
6 · The paper itself

Abstract

Transcription factor activity is largely regulated through post-translational modification. Here, we report the first integrative model of transcription that includes both interactions between transcription factors and promoters, and between transcription factors and modifying enzymes. Simulations indicate that our method is robust against noise. We validated our tool on a well-studied stress response network in yeast and on a STAT1-mediated regulatory network in human B cells. Our work represents a significant step toward a comprehensive model of gene transcription.

Indexed as

Gene Expression RegulationGene Regulatory NetworksModels, GeneticSoftwareTranscription, GeneticB-LymphocytesComputer SimulationDNA-Binding ProteinsHumansPromoter Regions, GeneticProtein KinasesSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSignal TransductionSTAT1 Transcription FactorTranscription FactorsDNA-Binding ProteinsMSN2 protein, S cerevisiaeMSN4 protein, S cerevisiaeProtein KinasesSaccharomyces cerevisiae ProteinsSTAT1 protein, humanSTAT1 Transcription FactorTranscription Factors

Identifiers

PMID21470963
PMCPMC3130287
OpenAlexW2161591754

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.