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‘Omics Approaches in Breast Cancer Research and Clinical Practice

Overview of attention for article published in Advances in Anatomic Pathology, November 2016
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Title
‘Omics Approaches in Breast Cancer Research and Clinical Practice
Published in
Advances in Anatomic Pathology, November 2016
DOI 10.1097/pap.0000000000000128
Pubmed ID
Authors

Priyakshi Kalita-de Croft, Fares Al-Ejeh, Amy E. McCart Reed, Jodi M. Saunus, Sunil R. Lakhani

Abstract

Our understanding of the natural history of breast cancer has evolved alongside technologies to study its genomic, transcriptomic, proteomic, and metabolomics landscapes. These technologies have helped decipher multiple molecular pathways dysregulated in breast cancer. First-generation 'omics analyses considered each of these dimensions individually, but it is becoming increasingly clear that more holistic, integrative approaches are required to fully understand complex biological systems. The 'omics represent an exciting era of discovery in breast cancer research, although important issues need to be addressed to realize the clinical utility of these data through precision cancer care. How can the data be applied to predict response to molecular-targeted therapies? When should treatment decisions be based on tumor genetics rather than histology? And with the sudden explosion of "big data" from large 'omics consortia and new precision clinical trials, how do we now negotiate evidence-based pathways to clinical translation through this apparent sea of opportunity? The aim of this review is to provide a broad overview of 'omics technologies used in breast cancer research today, the current state-of-play in terms of applying this new knowledge in the clinic, and the practical and ethical issues that will be central to the public discussion on the future of precision cancer care.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 13%
Student > Ph. D. Student 6 13%
Other 5 11%
Researcher 5 11%
Student > Bachelor 3 7%
Other 7 15%
Unknown 14 30%
Readers by discipline Count As %
Medicine and Dentistry 10 22%
Biochemistry, Genetics and Molecular Biology 8 17%
Computer Science 6 13%
Chemistry 2 4%
Economics, Econometrics and Finance 1 2%
Other 3 7%
Unknown 16 35%
Attention Score in Context

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 14 October 2016.
All research outputs
#17,285,668
of 25,374,647 outputs
Outputs from Advances in Anatomic Pathology
#428
of 552 outputs
Outputs of similar age
#205,210
of 317,808 outputs
Outputs of similar age from Advances in Anatomic Pathology
#2
of 6 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 552 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% 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 317,808 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.