Evidence map›Paper›PMID 20466809›Full record

ArticleNucleic acids research2010

Discovering modulators of gene expression.

Ozgün Babur, Emek Demir, Mithat Gönen, Chris Sander, Ugur Dogrusoz

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

23 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
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  3. Review
  4. Review
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  7. A Novel Small Peptide Inhibitor of NFOxidative medicine and cellular longevity · 2018
    Article
  8. Large-scale automated machine reading discovers new cancer-driving mechanisms.Database : the journal of biological databases and curation · 2018
    Article
  9. Article
  10. Article
  11. Inferring genome-wide functional modulatory network: a case study on NF-κB/RelA transcription factor.Journal of computational biology : a journal of computational molecular cell biology · 2015
    Article
  12. Article
  13. Article
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  15. Article
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  18. Using biological pathway data with paxtools.PLoS computational biology · 2013
    Article
  19. Article
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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

5 authors at 2 institutions in 2 countries.

Ozgün BaburCenter for Bioinformatics and Computer Engineering Department, Bilkent University, Ankara 06800, Turkey.
Emek Demir
Mithat Gönen
Chris Sander
Ugur Dogrusoz
Bilkent University · TRMemorial Sloan Kettering Cancer Center · US

Funding

Pathway Commons: Research Resource for Biological PathwaysP41HG004118 · NHGRI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2008 to 2011
$3.8M
NHGRI NIH HHS P41HG004118
6 · The paper itself

Abstract

Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein-protein interactions and transcription factor-target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes.

Indexed as

Gene Expression ProfilingGene Expression RegulationAlgorithmsModels, GeneticProbabilityProtein Interaction MappingReceptors, AndrogenTranscription FactorsTranscription, GeneticReceptors, AndrogenTranscription Factors

Identifiers

PMID20466809
PMCPMC2943625
OpenAlexW2036904266

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.