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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The 1-Particle-per-k-Nucleotides (1PkN) Elastic Network Model of DNA Dynamics with Sequence-Dependent Geometry
|
|---|---|
| Published in |
Frontiers in Physiology, March 2017
|
| DOI | 10.3389/fphys.2017.00103 |
| Pubmed ID | |
| Authors |
Takeru Kameda, Shuhei Isami, Yuichi Togashi, Hiraku Nishimori, Naoaki Sakamoto, Akinori Awazu |
| Abstract |
Coarse-grained models of DNA have made important contributions to the determination of the physical properties of genomic DNA, working as a molecular machine for gene regulation. In this study, to analyze the global dynamics of long DNA sequences with consideration of sequence-dependent geometry, we propose elastic network models of DNA where each particle represents k nucleotides (1-particle-per-k-nucleotides, 1PkN). The models were adjusted according to profiles of the anisotropic fluctuations obtained from our previous 1-particle-per-1-nucleotide (1P1N) model, which was proven to reproduce such profiles of all-atom models. We confirmed that the 1P3N and 1P4N models are suitable for the analysis of detailed dynamics such as local twisting motion. The models are intended for the analysis of large structures, e.g., 10-nm fibers in the nucleus, and nucleoids of mitochondrial or phage DNA at low computational costs. As an example, we surveyed the physical characteristics of the whole mitochondrial human and Plasmodium falciparum genomes. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 29% |
| Switzerland | 1 | 14% |
| France | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 38% |
| Professor | 2 | 25% |
| Student > Ph. D. Student | 2 | 25% |
| Student > Bachelor | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 2 | 25% |
| Biochemistry, Genetics and Molecular Biology | 2 | 25% |
| Physics and Astronomy | 2 | 25% |
| Chemistry | 1 | 13% |
| Unknown | 1 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 30 March 2021.
All research outputs
#7,657,233
of 25,104,329 outputs
Outputs from Frontiers in Physiology
#3,620
of 15,417 outputs
Outputs of similar age
#112,646
of 313,741 outputs
Outputs of similar age from Frontiers in Physiology
#69
of 229 outputs
Altmetric has tracked 25,104,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 15,417 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,741 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 229 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.