↓ Skip to main content

A HIF-1 network reveals characteristics of epithelial-mesenchymal transition in acute promyelocytic leukemia

Overview of attention for article published in Genome Medicine, December 2014
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
8 tweeters

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
26 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A HIF-1 network reveals characteristics of epithelial-mesenchymal transition in acute promyelocytic leukemia
Published in
Genome Medicine, December 2014
DOI 10.1186/s13073-014-0084-4
Pubmed ID
Authors

Stefano Percio, Nadia Coltella, Sara Grisanti, Rosa Bernardi, Linda Pattini

Abstract

Acute promyelocytic leukemia (APL) is a sub-type of acute myeloid leukemia (AML) characterized by a block of myeloid differentiation at the promyelocytic stage and the predominant t(15:17) chromosomal translocation. We have previously determined that cells from APL patients show increased expression of genes regulated by hypoxia-inducible transcription factors (HIFs) compared to normal promyelocytes. HIFs regulate crucial aspects of solid tumor progression and are currently being implicated in leukemogenesis.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 8%
Unknown 24 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Other 3 12%
Researcher 3 12%
Student > Master 3 12%
Student > Doctoral Student 2 8%
Other 4 15%
Unknown 6 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 27%
Agricultural and Biological Sciences 5 19%
Medicine and Dentistry 4 15%
Computer Science 2 8%
Engineering 2 8%
Other 0 0%
Unknown 6 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 January 2015.
All research outputs
#6,238,119
of 21,321,365 outputs
Outputs from Genome Medicine
#997
of 1,355 outputs
Outputs of similar age
#90,582
of 346,166 outputs
Outputs of similar age from Genome Medicine
#43
of 68 outputs
Altmetric has tracked 21,321,365 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,355 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.9. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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 346,166 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 73% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.