Evidence map›Paper›PMID 30668638›Full record

ArticleBioinformatics (Oxford, England)2019

CMEP: a database for circulating microRNA expression profiling.

Jian-Rong Li, Chun-Yip Tong, Tsai-Jung Sung, Ting-Yu Kang, Xianghong Jasmine Zhou, Chun-Chi Liu

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

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  15. Cancers · 2021
    Article
  16. Emerging roles of exosomal miRNAs in diabetes mellitus.Clinical and translational medicine · 2021
    Review
  17. Article
  18. Article
  19. Article
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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.

Jian-Rong LiInstitute of Genomics and Bioinformatics.
Chun-Yip TongInstitute of Genomics and Bioinformatics.
Tsai-Jung SungInstitute of Genomics and Bioinformatics.
Ting-Yu KangInstitute of Genomics and Bioinformatics.
Xianghong Jasmine ZhouDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, USA.
Chun-Chi LiuInstitute of Genomics and Bioinformatics.

Funding

The UCLA Center in Early Detection of Liver CancerU01CA230705 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Vatche Agopian, Samuel Wheeler French · 2018 to 2026
$6.6M
NCI NIH HHS U01 CA230705
6 · The paper itself

Abstract

motivationIn recent years, several experimental studies have revealed that the microRNAs (miRNAs) in serum, plasma, exosome and whole blood are dysregulated in various types of diseases, indicating that the circulating miRNAs may serve as potential noninvasive biomarkers for disease diagnosis and prognosis. However, no database has been constructed to integrate the large-scale circulating miRNA profiles, explore the functional pathways involved and predict the potential biomarkers using feature selection between the disease conditions. Although there have been several studies attempting to generate a circulating miRNA database, they have not yet integrated the large-scale circulating miRNA profiles or provided the biomarker-selection function using machine learning methods.

resultsTo fill this gap, we constructed the Circulating MicroRNA Expression Profiling (CMEP) database for integrating, analyzing and visualizing the large-scale expression profiles of phenotype-specific circulating miRNAs. The CMEP database contains massive datasets that were manually curated from NCBI GEO and the exRNA Atlas, including 66 datasets, 228 subsets and 10 419 samples. The CMEP provides the differential expression circulating miRNAs analysis and the KEGG functional pathway enrichment analysis. Furthermore, to provide the function of noninvasive biomarker discovery, we implemented several feature-selection methods, including ridge regression, lasso regression, support vector machine and random forests. Finally, we implemented a user-friendly web interface to improve the user experience and to visualize the data and results of CMEP. AVAILABILITY AND IMPLEMENTATION: CMEP is accessible at http://syslab5.nchu.edu.tw/CMEP.

Indexed as

Databases, FactualBiomarkersCirculating MicroRNAExosomesGene Expression ProfilingBiomarkersCirculating MicroRNA

Identifiers

PMID30668638
PMCPMC7963074

What OpenQuestion holds

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Registered trials

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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.