Evidence map›Paper›PMID 26679516›Full record

ArticleBMC systems biology2015

A model for gene deregulation detection using expression data.

Thomas Picchetti, Julien Chiquet, Mohamed Elati, Pierre Neuvial, Rémy Nicolle, Etienne Birmelé

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

6 authors at 2 institutions in 1 country.

Thomas Picchetti
Julien Chiquet
Mohamed Elati
Pierre Neuvial
Rémy Nicolle
Etienne Birmelé
Centre National de la Recherche Scientifique · FRDélégation Paris 5 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In tumoral cells, gene regulation mechanisms are severely altered. Genes that do not react normally to their regulators' activity can provide explanations for the tumoral behavior, and be characteristic of cancer subtypes. We thus propose a statistical methodology to identify the misregulated genes given a reference network and gene expression data.

Indexed as

Models, GeneticTranscriptomeAlgorithmsFalse Positive ReactionsGene Regulatory NetworksHumansUrinary Bladder Neoplasms

Identifiers

PMID26679516
PMCPMC4674863
OpenAlexW1847043871

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.