↓ Skip to main content

Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant…

Overview of attention for article published in Breast Cancer Research, September 2009
Altmetric Badge

Citations

dimensions_citation
93 Dimensions

Readers on

mendeley
123 Mendeley
citeulike
1 CiteULike
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
Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy
Published in
Breast Cancer Research, September 2009
DOI 10.1186/bcr2363
Pubmed ID
Authors

Silvia Darb-Esfahani, Sibylle Loibl, Berit M Müller, Marc Roller, Carsten Denkert, Martina Komor, Karsten Schlüns, Jens Uwe Blohmer, Jan Budczies, Bernd Gerber, Aurelia Noske, Andreas du Bois, Wilko Weichert, Christian Jackisch, Manfred Dietel, Klaus Richter, Manfred Kaufmann, Gunter von Minckwitz

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
United States 2 2%
Germany 1 <1%
Egypt 1 <1%
Mexico 1 <1%
Iran, Islamic Republic of 1 <1%
Japan 1 <1%
Georgia 1 <1%
Unknown 113 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 24%
Student > Ph. D. Student 18 15%
Student > Bachelor 11 9%
Other 9 7%
Student > Postgraduate 9 7%
Other 25 20%
Unknown 22 18%
Readers by discipline Count As %
Medicine and Dentistry 43 35%
Agricultural and Biological Sciences 28 23%
Biochemistry, Genetics and Molecular Biology 13 11%
Nursing and Health Professions 4 3%
Pharmacology, Toxicology and Pharmaceutical Science 3 2%
Other 7 6%
Unknown 25 20%