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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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https://doi.org/10.5281/zenodo...
Dataset . 2020
License: CC BY
Data sources: Sygma
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Life Sciences dataset used in INFORE project, part 2

Authors: Montagud, Arnau; Ponce de León, Miguel; Valencia, Alfonso;

Life Sciences dataset used in INFORE project, part 2

Abstract

Life Sciences dataset used in INFORE project, part 2 The dataset comprises the output of several simulations of a model of tumor growth with different parameter values. The model is a multi-scale agent-based model of a tumor spheroid that is treated with periodic pulses of the cytokine tumor necrosis factor (TNF). The multi-scale model simulates processes including i) the diffusion, uptake, and secretion of molecular entities such as oxygen, or TNF; ii) the mechanical interaction between cells; and iii) cellular processes including cell life cycle, cell death models, signal transduction. The multi-scale model was implemented and simulated using the PhysiBoSS framework (Letort et al. 2019). The dataset corresponds to different examples of parameters combinations of our use case that correspond to the different panels of Figure 4 in Documentation folder. This figure comes from the paper in the same folder. You can find a broad discussion of our use case in the Biological Use Case Documentation file. Also, The results of the cell simulations can be found in example_XXX/run0/outputs. The results of the microenvironment simulations can be found in example_XXX/run0/microutputs. Details on how these files are built can be found in Biological Use Case output format file (which is a snippet of the broad documentation file that I detached for your convenience). Briefly: each time step defined, the software writes an output and microutput file. For instance, ecm_t00030.txt correspond to time step 30. Each line of these files corresponds to a cell or microenvironment entity (oxygen, TNF, etc). Columns are defined by the first row for output folder. For the microutputs, the first three columns correspond to spatial coordinates and the fourth to the value of the density. The examples are: - example_spheroid_TNF_nopulse: corresponds to Figure 4 A. - example_spheroid_TNF_onepulse: corresponds to Figure 4 C. - example_spheroid_TNF_pulse150: corresponds to Figure 4 D left. This is the simulation outcome desired: proliferative cells die out with increasing number of pulses of TNF. - example_spheroid_TNF_pulse600: corresponds to Figure 4 D right. - example_spheroid_TNF_pulsecont: corresponds to Figure 4 B. - example_cells_with_ECM_mutants: does NOT correspond to Figure 4. This is an example in which microutput folder is full of two entities: oxygen and ECM. Also, in this example you can find a folder (ECM_mut) with the kind of visualisation that we perform to showcase results. - example_spheroid_TNF_pulsecont_oxy: 21 simulations with slightly different oxygen tolerance conditions using as a base the simulation with one continuous pulse (Figure 4 B from the presentation). The only difference among parameters file is the "oxygen_necrotic" value, which controls the threshold above which cells commit to necrosis due to lack of oxygen. In the original simulation this value was zero and the maximum available oxygen is 40 fg/µm^3. Here, we have studied the parameter value from 0 to 40 in steps of 5.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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