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Derivation and characterization of matched cell lines from primary and recurrent serous ovarian cancer

Overview of attention for article published in BMC Cancer, August 2012
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1 tweeter

Citations

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Readers on

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39 Mendeley
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1 CiteULike
Title
Derivation and characterization of matched cell lines from primary and recurrent serous ovarian cancer
Published in
BMC Cancer, August 2012
DOI 10.1186/1471-2407-12-379
Pubmed ID
Authors

Isabelle J Létourneau, Michael CJ Quinn, Lu-Lin Wang, Lise Portelance, Katia Y Caceres, Louis Cyr, Nathalie Delvoye, Liliane Meunier, Manon de Ladurantaye, Zhen Shen, Suzanna L Arcand, Patricia N Tonin, Diane M Provencher, Anne-Marie Mes-Masson

Abstract

Cell line models have proven to be effective tools to investigate a variety of ovarian cancer features. Due to the limited number of cell lines, particularly of the serous subtype, the heterogeneity of the disease, and the lack of cell lines that model disease progression, there is a need to further develop cell line resources available for research. This study describes nine cell lines derived from three ovarian cancer cases that were established at initial diagnosis and at subsequent relapse after chemotherapy.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 3%
United States 1 3%
Pakistan 1 3%
Colombia 1 3%
Canada 1 3%
Unknown 34 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Researcher 8 21%
Student > Master 6 15%
Student > Bachelor 4 10%
Professor > Associate Professor 3 8%
Other 10 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 38%
Medicine and Dentistry 8 21%
Unspecified 5 13%
Biochemistry, Genetics and Molecular Biology 4 10%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 5 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 August 2012.
All research outputs
#3,174,255
of 4,504,945 outputs
Outputs from BMC Cancer
#1,525
of 2,430 outputs
Outputs of similar age
#51,483
of 78,307 outputs
Outputs of similar age from BMC Cancer
#52
of 86 outputs
Altmetric has tracked 4,504,945 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,430 research outputs from this source. They receive a mean Attention Score of 2.4. 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 78,307 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.