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The tumor as an organ: comprehensive spatial and temporal modeling of the tumor and its microenvironment

Overview of attention for article published in BMC Bioinformatics, August 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

blogs
1 blog
twitter
7 X users

Citations

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12 Dimensions

Readers on

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28 Mendeley
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Title
The tumor as an organ: comprehensive spatial and temporal modeling of the tumor and its microenvironment
Published in
BMC Bioinformatics, August 2016
DOI 10.1186/s12859-016-1168-5
Pubmed ID
Authors

Naamah Bloch, David Harel

Abstract

Research related to cancer is vast, and continues in earnest in many directions. Due to the complexity of cancer, a better understanding of tumor growth dynamics can be gleaned from a dynamic computational model. We present a comprehensive, fully executable, spatial and temporal 3D computational model of the development of a cancerous tumor together with its environment. The model was created using Statecharts, which were then connected to an interactive animation front-end that we developed especially for this work, making it possible to visualize on the fly the on-going events of the system's execution, as well as the effect of various input parameters. We were thus able to gain a better understanding of, e.g., how different amounts or thresholds of oxygen and VEGF (vascular endothelial growth factor) affect the progression of the tumor. We found that the tumor has a critical turning point, where it either dies or recovers. If minimum conditions are met at that time, it eventually develops into a full, active, growing tumor, regardless of the actual amount; otherwise it dies. This brings us to the conclusion that the tumor is in fact a very robust system: changing initial values of VEGF and oxygen can increase the time it takes to become fully developed, but will not necessarily completely eliminate it.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Brazil 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 36%
Student > Ph. D. Student 7 25%
Student > Master 3 11%
Student > Bachelor 2 7%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 18%
Biochemistry, Genetics and Molecular Biology 4 14%
Computer Science 4 14%
Medicine and Dentistry 2 7%
Engineering 2 7%
Other 7 25%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 12 December 2016.
All research outputs
#2,822,153
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#914
of 7,418 outputs
Outputs of similar age
#49,499
of 343,695 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 133 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,418 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 done well, scoring higher than 87% 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 343,695 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 133 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.