Evidence map›Paper›PMID 27213352›Full record

ArticleInternational journal of molecular sciences2016

Predicting MicroRNA Biomarkers for Cancer Using Phylogenetic Tree and Microarray Analysis.

Hsiuying Wang

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. The Human Pre-miRNA Distance Distribution for Exploring Disease Association.International journal of molecular sciences · 2023
    Article
  6. Article
  7. Article
  8. MicroRNAs, Multiple Sclerosis, and Depression.International journal of molecular sciences · 2021
    Review
  9. MicroRNAs, Parkinson's Disease, and Diabetes Mellitus.International journal of molecular sciences · 2021
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Anti-NMDA Receptor Encephalitis and Vaccination.International journal of molecular sciences · 2017
    Article
  16. 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

1 author.

Hsiuying WangInstitute of Statistics, National Chiao Tung University, Hsinchu 30010, Taiwan. wang@stat.nctu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are shown to be involved in the initiation and progression of cancers in the literature, and the expression of miRNAs is used as an important cancer prognostic tool. The aim of this study is to predict high-confidence miRNA biomarkers for cancer. We adopt a method that combines miRNA phylogenetic structure and miRNA microarray data analysis to discover high-confidence miRNA biomarkers for colon, prostate, pancreatic, lung, breast, bladder and kidney cancers. There are 53 miRNAs selected through this method that either have potential to involve a single cancer's development or to involve several cancers' development. These miRNAs can be used as high-confidence miRNA biomarkers of these seven investigated cancers for further experiment validation. miR-17, miR-20, miR-106a, miR-106b, miR-92, miR-25, miR-16, miR-195 and miR-143 are selected to involve a single cancer's development in these seven cancers. They have the potential to be useful miRNA biomarkers when the result can be confirmed by experiments.

Indexed as

Biomarkers, TumorMicroRNAsNeoplasmsOligonucleotide Array Sequence AnalysisPhylogenyRNA, NeoplasmFemaleHumansMaleBiomarkers, TumorMicroRNAsRNA, NeoplasmcancermicroarraymicroRNAphylogenetic treesequence

Identifiers

PMID27213352
PMCPMC4881592

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.