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Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences1

Overview of attention for article published in bioRxiv, February 2018
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Title
Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences1
Published in
bioRxiv, February 2018
DOI 10.1101/261081
Authors

Richard Karlsson Linnér, Pietro Biroli, Edward Kong, S Fleur W Meddens, Robbee Wedow, Mark Alan Fontana, Maël Lebreton, Abdel Abdellaoui, Anke R Hammerschlag, Michel G Nivard, Aysu Okbay, Cornelius A Rietveld, Pascal N Timshel, Stephen P Tino, Maciej Trzaskowski, Ronald de Vlaming, Christian L Zünd, Yanchun Bao, Laura Buzdugan, Ann H Caplin, Chia-Yen Chen, Peter Eibich, Pierre Fontanillas, Juan R Gonzalez, Peter K Joshi, Ville Karhunen, Aaron Kleinman, Remy Z Levin, Christina M Lill, Gerardus A Meddens, Gerard Muntané, Sandra Sanchez-Roige, Frank J van Rooij, Erdogan Taskesen, Yang Wu, Futao Zhang, International Cannabis Consortium eQTLgen Consortium, Adam Auton, Jason D Boardman, David W Clark, Andrew Conlin, Conor C Dolan, Urs Fischbacher, Patrick JF Groenen, Kathleen Mullan Harris, Gregor Hasler, Albert Hofman, Mohammad A Ikram, Sonia Jain, Robert Karlsson, Ronald C Kessler, Maarten Kooyman, James MacKillop, Minna Männikkö, Carlos Morcillo-Suarez, Matthew B McQueen, Klaus M Schmidt, Melissa C Smart, Matthias Sutter, A Roy Thurik, Andre G Uitterlinden, Jon White, Harriet de Wit, Jian Yang, Lars Bertram, Dorret Boomsma, Tõnu Esko, Ernst Fehr, David A Hinds, Magnus Johannesson, Meena Kumari, David Laibson, Patrik KE Magnusson, Michelle N Meyer, Arcadi Navarro, Abraham A Palmer, Tune H Pers, Danielle Posthuma, Daniel Schunk, Murray B Stein, Rauli Svento, Henning Tiemeier, Paul RHJ Timmers, Patrick Turley, Robert J Ursano, Gert G Wagner, James F Wilson, Jacob Gratten, James J Lee, David Cesarini, Daniel J Benjamin, Philipp D Koellinger, Jonathan P Beauchamp

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 15%
Student > Ph. D. Student 6 13%
Other 1 2%
Professor 1 2%
Student > Master 1 2%
Other 1 2%
Unknown 30 64%
Readers by discipline Count As %
Social Sciences 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Neuroscience 2 4%
Mathematics 1 2%
Computer Science 1 2%
Other 4 9%
Unknown 34 72%