Evidence map›Paper›PMID 28472271›Full record

ArticleBioinformatics (Oxford, England)2017

Annotating function to differentially expressed LincRNAs in myelodysplastic syndrome using a network-based method.

Keqin Liu, Dominik Beck, Julie A I Thoms, Liang Liu, Weiling Zhao, John E Pimanda, Xiaobo Zhou

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Keqin LiuDepartment of Radiology, Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
Dominik BeckLowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, 2052, Australia.
Julie A I ThomsLowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, 2052, Australia.
Liang LiuDepartment of Radiology, Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
Weiling ZhaoDepartment of Radiology, Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
John E PimandaLowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, 2052, Australia.
Xiaobo ZhouDepartment of Radiology, Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
Wake Forest University · USUNSW Sydney · AUPrince of Wales Hospital · AU

Funding

Systems Modeling Guided Bone regenerationU01AR069395 · NIAMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI YANG, YUNZHI, ZHOU, XIAOBO · 2016 to 2021
$3.4M
Modelling the Growth of the MIC Niche at the System LevelU01CA166886 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO · 2012 to 2016
$2.2M
Integrative approach to studying LncRNA functionsR01GM123037 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2017 to 2020
$1.5M
System Biology Approach for Signaling Transduction Study of Complex PhenotypesR01LM010185 · NLM · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO, ZU, YOULI · 2009 to 2012
$1.3M
itNETZ: Integrative and Translational Network-based Cellular Signature AnalyzerU01HL111560 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO · 2011 to 2013
$1.1M
NCI NIH HHS U01 CA166886NHLBI NIH HHS U01 HL111560NIAMS NIH HHS U01 AR069395NIGMS NIH HHS R01 GM123037NLM NIH HHS R01 LM010185
6 · The paper itself

Abstract

motivationLong non-coding RNAs (lncRNAs) have been implicated in the regulation of diverse biological functions. The number of newly identified lncRNAs has increased dramatically in recent years but their expression and function have not yet been described from most diseases. To elucidate lncRNA function in human disease, we have developed a novel network based method (NLCFA) integrating correlations between lncRNA, protein coding genes and noncoding miRNAs. We have also integrated target gene associations and protein-protein interactions and designed our model to provide information on the combined influence of mRNAs, lncRNAs and miRNAs on cellular signal transduction networks.

resultsWe have generated lncRNA expression profiles from the CD34+ haematopoietic stem and progenitor cells (HSPCs) from patients with Myelodysplastic syndromes (MDS) and healthy donors. We report, for the first time, aberrantly expressed lncRNAs in MDS and further prioritize biologically relevant lncRNAs using the NLCFA. Taken together, our data suggests that aberrant levels of specific lncRNAs are intimately involved in network modules that control multiple cancer-associated signalling pathways and cellular processes. Importantly, our method can be applied to prioritize aberrantly expressed lncRNAs for functional validation in other diseases and biological contexts. AVAILABILITY AND IMPLEMENTATION: The method is implemented in R language and Matlab. CONTACT: xizhou@wakehealth.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Signal TransductionSoftwareAgedGene Expression ProfilingGene Expression RegulationHumansMicroRNAsMiddle AgedMolecular Sequence AnnotationMyelodysplastic SyndromesNeoplasmsOligonucleotide Array Sequence AnalysisRNA, Long NoncodingRNA, MessengerSequence Analysis, RNAMicroRNAsRNA, Long NoncodingRNA, Messenger

Identifiers

PMID28472271
PMCPMC5860060
OpenAlexW2610367707

What OpenQuestion holds

Textmetadata
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.