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Cold Spring Harbor Laboratory Press

Opportunities and obstacles for deep learning in biology and medicine

Overview of attention for article published in bioRxiv, May 2017
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1228 Mendeley
3 CiteULike
Opportunities and obstacles for deep learning in biology and medicine
Published in
bioRxiv, May 2017
DOI 10.1101/142760

Travers Ching, Daniel S. Himmelstein, Brett K. Beaulieu-Jones, Alexandr A. Kalinin, Brian T., Gregory P. Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M. Hoffman, Wei Xie, Gail L. Rosen, Benjamin J. Lengerich, Johnny Israeli, Jack Lanchantin, Stephen Woloszynek, Anne E. Carpenter, Avanti Shrikumar, Jinbo Xu, Evan M. Cofer, Christopher A. Lavender, Srinivas C. Turaga, Amr M. Alexandari, Zhiyong Lu, David J. Harris, Dave DeCaprio, Yanjun Qi, Anshul Kundaje, Yifan Peng, Laura K. Wiley, Marwin H.S. Segler, Simina M. Boca, S. Joshua Swamidass, Austin Huang, Anthony Gitter, Casey S. Greene

X Demographics

X Demographics

The data shown below were collected from the profiles of 814 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,228 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 <1%
United Kingdom 2 <1%
United States 2 <1%
Spain 1 <1%
Uruguay 1 <1%
Unknown 1220 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 222 18%
Researcher 203 17%
Student > Master 117 10%
Student > Bachelor 69 6%
Other 54 4%
Other 145 12%
Unknown 418 34%
Readers by discipline Count As %
Computer Science 240 20%
Biochemistry, Genetics and Molecular Biology 144 12%
Agricultural and Biological Sciences 141 11%
Engineering 72 6%
Medicine and Dentistry 46 4%
Other 147 12%
Unknown 438 36%