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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A semi-local neighborhood-based framework for probabilistic cell lineage tracing
|
|---|---|
| Published in |
BMC Bioinformatics, June 2014
|
| DOI | 10.1186/1471-2105-15-217 |
| Pubmed ID | |
| Authors |
Anthony Santella, Zhuo Du, Zhirong Bao |
| Abstract |
Advances in fluorescence labeling and imaging have made it possible to acquire in vivo records of complex biological processes. Analysis has lagged behind acquisition in part because of the difficulty and computational expense of accurate cell tracking. In vivo analysis requires, at minimum, tracking hundreds of cells over hundreds of time points in complex three dimensional environments. We address this challenge with a computational framework capable of efficiently and accurately tracing entire cell lineages. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Norway | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| Unknown | 30 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 26% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Doctoral Student | 3 | 10% |
| Professor | 3 | 10% |
| Student > Bachelor | 2 | 6% |
| Other | 6 | 19% |
| Unknown | 5 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 32% |
| Computer Science | 5 | 16% |
| Biochemistry, Genetics and Molecular Biology | 3 | 10% |
| Neuroscience | 3 | 10% |
| Engineering | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 7 | 23% |
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 11 June 2020.
All research outputs
#6,940,770
of 22,757,541 outputs
Outputs from BMC Bioinformatics
#2,682
of 7,272 outputs
Outputs of similar age
#66,554
of 227,908 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 151 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,272 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 61% 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 227,908 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 69% of its contemporaries.
We're also able to compare this research output to 151 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 65% of its contemporaries.