Evidence map›Paper›PMID 25874214›Full record

ArticleBioMed research international2015

Identification of subtype specific miRNA-mRNA functional regulatory modules in matched miRNA-mRNA expression data: multiple myeloma as a case.

Yunpeng Zhang, Wei Liu, Yanjun Xu, Chunquan Li, Yingying Wang, Haixiu Yang, Chunlong Zhang, Fei Su, Yixue Li, Xia Li

Abstract read
In one paragraph

Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. MicroRNAs in multiple myeloma and related bone disease.Annals of translational medicine · 2015
    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

10 authors.

Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Wei LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China ; Department of Mathematics, Heilongjiang Institute of Technology, Harbin 150050, China.ORCID 0000-0003-3434-2968
Yanjun XuCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Chunquan LiCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Yingying WangCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.ORCID 0000-0003-0745-8850
Haixiu YangCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Fei SuCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Yixue LiCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong algorithm and multiobjective genetic algorithm to identify subtype specific miRNA-mRNA functional regulatory modules (MFRMs) through integrative analysis of three biological data sets: GO biological processes, miRNA target information, and matched miRNA and mRNA expression data. We applied our method on a heterogeneous disease, multiple myeloma (MM), to identify MM subtype specific MFRMs. The constructed miRNA-mRNA regulatory networks provide modular outlook at subtype specific miRNA-mRNA interactions. Furthermore, clustering analysis demonstrated that heterogeneous MFRMs were able to separate corresponding MM subtypes. These subtype specific MFRMs may aid in the further elucidation of the pathogenesis of each subtype and may serve to guide MM subtype diagnosis and treatment.

Indexed as

Databases, GeneticGene Expression Regulation, NeoplasticMicroRNAsMultiple MyelomaRNA, MessengerRNA, NeoplasmHumansMicroRNAsRNA, MessengerRNA, Neoplasm

Identifiers

PMID25874214
PMCPMC4385567

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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.