Evidence map›Paper›PMID 22039400›Full record

ArticlePloS one2011

miRNA regulatory circuits in ES cells differentiation: a chemical kinetics modeling approach.

Zijun Luo, Xuping Xu, Peili Gu, David Lonard, Preethi H Gunaratne, Austin J Cooney, Robert Azencott

Open access · goldAbstract readValidation Study
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
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

7 authors at 3 institutions in 1 country.

Zijun LuoDepartment of Mathematics, University of Houston, Houston, Texas, United States of America. boluomiduo1@gmail.com
Xuping Xu
Peili Gu
David Lonard
Preethi H Gunaratne
Austin J Cooney
Robert Azencott
Baylor College of Medicine · USUniversity of Houston · USThe University of Texas Health Science Center at Houston · US

Funding

The Role of p53 in Human Embryonic Stem CellsP01GM081627 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI SONGYANG, ZHOU · 2007 to 2011
$9.9M
NIGMS NIH HHS P01 GM081627NIGMS NIH HHS P01-GM081627-01
6 · The paper itself

Abstract

MicroRNAs (miRNAs) play an important role in gene regulation for Embryonic Stem cells (ES cells), where they either down-regulate target mRNA genes by degradation or repress protein expression of these mRNA genes by inhibiting translation. Well known tables TargetScan and miRanda may predict quite long lists of potential miRNAs inhibitors for each mRNA gene, and one of our goals was to strongly narrow down the list of mRNA targets potentially repressed by a known large list of 400 miRNAs. Our paper focuses on algorithmic analysis of ES cells microarray data to reliably detect repressive interactions between miRNAs and mRNAs. We model, by chemical kinetics equations, the interaction architectures implementing the two basic silencing processes of miRNAs, namely "direct degradation" or "translation inhibition" of targeted mRNAs. For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data. When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction. This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation.

Indexed as

Cell DifferentiationModels, BiologicalAnimalsBlotting, WesternEmbryonic Stem CellsKineticsMiceMicroRNAsOligonucleotide Array Sequence AnalysisTranscription, GeneticMicroRNAs

Identifiers

PMID22039400
PMCPMC3198445
OpenAlexW2097595390

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.