↓ Skip to main content

Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos

Overview of attention for article published in BMC Biology, December 2016
Altmetric Badge

Mentioned by

twitter
6 X users

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
59 Mendeley
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
Quantitative imaging of mammalian transcriptional dynamics: from single cells to whole embryos
Published in
BMC Biology, December 2016
DOI 10.1186/s12915-016-0331-9
Pubmed ID
Authors

Ziqing W. Zhao, Melanie D. White, Stephanie Bissiere, Valeria Levi, Nicolas Plachta

Abstract

Probing dynamic processes occurring within the cell nucleus at the quantitative level has long been a challenge in mammalian biology. Advances in bio-imaging techniques over the past decade have enabled us to directly visualize nuclear processes in situ with unprecedented spatial and temporal resolution and single-molecule sensitivity. Here, using transcription as our primary focus, we survey recent imaging studies that specifically emphasize the quantitative understanding of nuclear dynamics in both time and space. These analyses not only inform on previously hidden physical parameters and mechanistic details, but also reveal a hierarchical organizational landscape for coordinating a wide range of transcriptional processes shared by mammalian systems of varying complexity, from single cells to whole embryos.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 2%
United States 1 2%
France 1 2%
Unknown 56 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 31%
Student > Master 8 14%
Researcher 7 12%
Student > Doctoral Student 5 8%
Professor > Associate Professor 4 7%
Other 6 10%
Unknown 11 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 36%
Biochemistry, Genetics and Molecular Biology 16 27%
Physics and Astronomy 4 7%
Chemistry 3 5%
Medicine and Dentistry 2 3%
Other 1 2%
Unknown 12 20%