Evidence map›Paper›PMID 24163754›Full record

ArticleMicroarrays (Basel, Switzerland)2013

Challenges for MicroRNA Microarray Data Analysis.

Bin Wang, Yaguang Xi

Abstract read
In one paragraph

Article in Microarrays (Basel, Switzerland), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
–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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. A Post-Processing Algorithm for miRNA Microarray Data.International journal of molecular sciences · 2020
    Article
  12. Review
  13. miRNAs in the Diagnosis and Prognosis of Skin Cancer.Frontiers in cell and developmental biology · 2020
    Review
  14. Label-Free MicroRNA Optical Biosensors.Nanomaterials (Basel, Switzerland) · 2019
    Review
  15. Potential Fluid Biomarkers for the Diagnosis of Mild Cognitive Impairment.International journal of molecular sciences · 2019
    Review
  16. Article
  17. Review
  18. A Circulating MicroRNA Signature Serves as a Diagnostic and Prognostic Indicator in Sarcoidosis.American journal of respiratory cell and molecular biology · 2018
    Article
  19. MicroRNAs as biomarkers for liver injury: Current knowledge, challenges and future prospects.Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2017
    Review
  20. 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

2 authors.

Bin WangDepartment of Mathematics and Statistics, University of South Alabama, 411 University BLVD N, Room 325, Mobile, AL 36688, USA; bwang@southalabama.edu.
Yaguang Xi

Funding

MicroRNA, sulindac, and breast cancer chemopreventionR21CA160280 · NCI · UNIVERSITY OF SOUTH ALABAMA · PI PIAZZA, GARY A, XI, YAGUANG · 2012 to 2013
$346k
NCI NIH HHS R21 CA160280
6 · The paper itself

Abstract

Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels) to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1) the total number of target genes is large enough (>10,000); and (2) the expression level of the majority of genes is kept constant. However, microRNA (miRNA) arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays.

Indexed as

bead arraymeasurement errormicroarraymicroRNAnormalizationqRT-PCR

Identifiers

PMID24163754
PMCPMC3807239

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.