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Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice

Overview of attention for article published in BMC Biology, October 2013
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Title
Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice
Published in
BMC Biology, October 2013
DOI 10.1186/1741-7007-11-106
Pubmed ID
Authors

Jean-François Schmouth, Mauro Castellarin, Stéphanie Laprise, Kathleen G Banks, Russell J Bonaguro, Simone C McInerny, Lisa Borretta, Mahsa Amirabbasi, Andrea J Korecki, Elodie Portales-Casamar, Gary Wilson, Lisa Dreolini, Steven JM Jones, Wyeth W Wasserman, Daniel Goldowitz, Robert A Holt, Elizabeth M Simpson

Abstract

The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome') strategy to expand our understanding of human gene regulation in vivo.

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The data shown below were collected from the profiles of 9 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 19%
Researcher 3 14%
Student > Ph. D. Student 3 14%
Student > Postgraduate 2 10%
Professor > Associate Professor 2 10%
Other 3 14%
Unknown 4 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 29%
Biochemistry, Genetics and Molecular Biology 5 24%
Medicine and Dentistry 2 10%
Psychology 1 5%
Immunology and Microbiology 1 5%
Other 0 0%
Unknown 6 29%