| Title |
Tumorcode
|
|---|---|
| Published in |
The European Physical Journal E, April 2018
|
| DOI | 10.1140/epje/i2018-11659-x |
| Pubmed ID | |
| Authors |
Thierry Fredrich, Michael Welter, Heiko Rieger |
| Abstract |
During the past years our group published several articles using computer simulations to address the complex interaction of tumors and the vasculature as underlying transport network. Advances in imaging and lab techniques pushed in vitro research of tumor spheroids forward and animal models as well as clinical studies provided more insights to single processes taking part in tumor growth, however, an overall picture is still missing. Computer simulations are a non-invasive option to cumulate current knowledge and form a quasi in vivo system. In our software, several known models were assembled into a multi-scale approach which allows to study length scales relevant for clinical applications. We release our code to the public domain, together with a detailed description of the implementation and several examples, with the hope of usage and futher development by the community. A justification for the included algorithms and the biological models was obtained in previous publications, here we summarize the technical aspects following the workflow of a typical simulation procedure. |
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 States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 44% |
| Professor | 2 | 13% |
| Student > Doctoral Student | 1 | 6% |
| Student > Bachelor | 1 | 6% |
| Researcher | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 3 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 31% |
| Biochemistry, Genetics and Molecular Biology | 3 | 19% |
| Physics and Astronomy | 2 | 13% |
| Computer Science | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 2 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 30. 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 08 April 2019.
All research outputs
#1,154,345
of 23,498,099 outputs
Outputs from The European Physical Journal E
#68
of 650 outputs
Outputs of similar age
#26,990
of 327,781 outputs
Outputs of similar age from The European Physical Journal E
#5
of 22 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 650 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 89% of its peers.
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We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.