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Dove Medical Press

Identification of key genes and molecular mechanisms associated with dedifferentiated liposarcoma based on bioinformatic methods

Overview of attention for article published in OncoTargets and therapy, June 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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6 X users
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1 Facebook page

Citations

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9 Dimensions

Readers on

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11 Mendeley
Title
Identification of key genes and molecular mechanisms associated with dedifferentiated liposarcoma based on bioinformatic methods
Published in
OncoTargets and therapy, June 2017
DOI 10.2147/ott.s132071
Pubmed ID
Authors

Hongliang Yu, Dong Pei, Longyun Chen, Xiaoxiang Zhou, Haiwen Zhu

Abstract

Dedifferentiated liposarcoma (DDLPS) is one of the most deadly types of soft tissue sarcoma. To date, there have been few studies dedicated to elucidating the molecular mechanisms behind the disease; therefore, the molecular mechanisms behind this malignancy remain largely unknown. Microarray profiles of 46 DDLPS samples and nine normal fat controls were extracted from Gene Expression Omnibus (GEO). Quality control for these microarray profiles was performed before analysis. Hierarchical clustering and principal component analysis were used to distinguish the general differences in gene expression between DDLPS samples and the normal fat controls. Differentially expressed genes (DEGs) were identified using the Limma package in R. Next, the enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained using the online tool DAVID (http://david.abcc.ncifcrf.gov/). A protein-protein interaction (PPI) network was constructed using the STRING database and Cytoscape software. Furthermore, the hub genes within the PPI network were identified. All 55 microarray profiles were confirmed to be of high quality. The gene expression pattern of DDLPS samples was significantly different from that of normal fat controls. In total, 700 DEGs were identified, and 83 enriched GO terms and three KEGG pathways were obtained. Specifically, within the DEGs of DDLPS samples, several pathways were identified as being significantly enriched, including the PPAR signaling pathway, cell cycle pathway, and pyruvate metabolism pathway. Furthermore, the dysregulated PPI network of DDLPS was constructed, and 14 hub genes were identified. Characteristic of DDLPS, the genes CDK4 and MDM2 were universally found to be up-regulated and amplified in gene copy number. This study used bioinformatics to comprehensively mine DDLPS microarray data in order to obtain a deeper understanding of the molecular mechanism of DDLPS.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 18%
Researcher 2 18%
Student > Bachelor 1 9%
Lecturer 1 9%
Professor > Associate Professor 1 9%
Other 0 0%
Unknown 4 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 18%
Medicine and Dentistry 2 18%
Biochemistry, Genetics and Molecular Biology 1 9%
Immunology and Microbiology 1 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 9%
Other 0 0%
Unknown 4 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 June 2017.
All research outputs
#5,817,478
of 23,577,654 outputs
Outputs from OncoTargets and therapy
#273
of 2,977 outputs
Outputs of similar age
#90,416
of 317,486 outputs
Outputs of similar age from OncoTargets and therapy
#8
of 77 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,977 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,486 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.