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A new application of the phase-field method for understanding the mechanisms of nuclear architecture reorganization

Overview of attention for article published in Journal of Mathematical Biology, May 2016
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Title
A new application of the phase-field method for understanding the mechanisms of nuclear architecture reorganization
Published in
Journal of Mathematical Biology, May 2016
DOI 10.1007/s00285-016-1031-3
Pubmed ID
Authors

S. Seirin Lee, S. Tashiro, A. Awazu, R. Kobayashi

Abstract

Specific features of nuclear architecture are important for the functional organization of the nucleus, and chromatin consists of two forms, heterochromatin and euchromatin. Conventional nuclear architecture is observed when heterochromatin is enriched at nuclear periphery, and it represents the primary structure in the majority of eukaryotic cells, including the rod cells of diurnal mammals. In contrast to this, inverted nuclear architecture is observed when the heterochromatin is distributed at the center of the nucleus, which occurs in the rod cells of nocturnal mammals. The inverted architecture found in the rod cells of the adult mouse is formed through the reorganization of conventional architecture during terminal differentiation. Although a previous experimental approach has demonstrated the relationship between these two nuclear architecture types at the molecular level, the mechanisms underlying long-range reorganization processes remain unknown. The details of nuclear structures and their spatial and temporal dynamics remain to be elucidated. Therefore, a comprehensive approach, using mathematical modeling, is required, in order to address these questions. Here, we propose a new mathematical approach to the understanding of nuclear architecture dynamics using the phase-field method. We successfully recreated the process of nuclear architecture reorganization, and showed that it is robustly induced by physical features, independent of a specific genotype. Our study demonstrates the potential of phase-field method application in the life science fields.

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Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 32%
Researcher 6 24%
Student > Master 2 8%
Professor 2 8%
Unspecified 1 4%
Other 2 8%
Unknown 4 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 32%
Mathematics 3 12%
Physics and Astronomy 3 12%
Agricultural and Biological Sciences 3 12%
Materials Science 2 8%
Other 2 8%
Unknown 4 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2016.
All research outputs
#20,330,976
of 22,875,477 outputs
Outputs from Journal of Mathematical Biology
#545
of 658 outputs
Outputs of similar age
#291,271
of 338,744 outputs
Outputs of similar age from Journal of Mathematical Biology
#12
of 15 outputs
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So far Altmetric has tracked 658 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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