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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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Data for: Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity

Authors: Büscher, Tobias; Gompper, Gerhard; Elgeti, Jens;

Data for: Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity

Abstract

Tissue evolution: mechanical interplay of adhesion, pressure, and heterogeneity Full Data for corresponding publication. All folders are named by the actual simulation values used, not by the rescaled values shown in the paper All folders contain data files, trajectory files are converted and zipped, as well as the executable and the starting configuration file. Start simulations with ./cell_dpd starting_configuration.sconf The simulation for Fig.1 can be found in folder /free_evolution/ folder structure: /free_evolution/LXxLYxLZ/GB_F1/DeltaG_alpha/ with LX, LY, LZ simulation box lengths in x,y,z direction, GB and F1 the simulation parameters of the host tissue, DeltaG difference in G of neighbouring species and alpha the relative change of f1 to G of neighbouring species. The simulation for Fig.2 and Fig.S3 can be found in folder /heterogeneity/sharp_treshold/ folder structure: /heterogeneity/sharp_treshold/pm/tradeoff/ with mutation probability pm and tradeoff parameter between changes in G and F1. The simulation for Fig.S1 can be found in folder /heterogeneity/division_rate/tradeoff/ with tradeoff parameter between changes in G and F1. The simulation for the division rate simulations of Fig.S2 can be found in folder /pair_competition/12x12x12/40_6.0/division_rate/ The simulation for Figs. 4, 5 and S4 can be found in folder /pair_competition/12x12x12/40_6.0/sharp_treshold/ folder structure: /pair_competition/LXxLYxLZ/GW_F1W/sharp_treshold/GM/F1M/ with LX, LY, LZ simulation box lengths in x,y,z direction, GW and F1W the simulation parameters of host tissue and vice versa for mutant (M). The simulations for Fig.6 can be found in folder /mutationrate/ folder structure: /mutationrate/LXxLYxLZ/GW_F1W/pm/GM/F1M/ with LX, LY, LZ simulation box lengths in x,y,z direction, GW and F1W the simulation parameters of host tissue and vice versa for mutant (M) and mutation probability pm. The simulations for Fig.7 can be found in folder /survival/ folder structure: /survival/LXxLYxLZ/GW_F1W/GM/F1M/ with LX, LY, LZ simulation box lengths in x,y,z direction, GW and F1W the simulation parameters of host tissue and vice versa for mutant (M). The simulation for Fig.S5 can be found in folder /unstable/ folder structure: /unstable/LXxLYxLZ/GW_F1W/GM/F1M/phi0/sim_number with LX, LY, LZ simulation box lengths in x,y,z direction, GW and F1W the simulation parameters of host tissue and vice versa for mutant (M), initial number fraction phi0 and simulation number sim_number Folder /scripts/ contains all scripts to analyze the simulation results, described in the following: get_phi.py : Outputs file with cell number fractions from input file containing absolute cell numbers. Called by : python get_phi.py input output input: Name input file (in all simulations numcells.dat) output: Name output file minimize_uid: Outputs minimized trajectory file as input.min Called by: ./minimize_uid input input: name trajectory file (in all simulations traj.dat) convert2xyz_spec: Outputs trajectory in xyz format as input.xyz for pair competitions with n=2 Called by : ./convert2xyz_spec input input: name trajectory file (minimized file from minimize_uid) convert2xyz_new: Outputs trajectory in xyz format as input.xyz for heterogeneity simulations for n=21 species Called by : ./convert2xyz_new input input: name trajectory file (minimized file from minimize_uid) block_average.py : Outputs file with block averaged value from input file. Called by : python block_average.py input output column n_or_t t_n_start t_n_end input: Name input file output: Output file name column: column to be averaged n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end t_n_start: time/line number to start average t_n_end: time/line number to end average. If not given, t_n_start is interpreted, how much time/many line numbers to go back from the end cluster_analysis.py : Number of clusters of each species, cluster analysis by DB-SCAN algorithm with minimal points=1 and potential cut-off distance as size treshold Called by: python cluster_analysis.py input output input: trajectory file in xyz format output: name of output file neighbour_analysis.py : Analysis of the cell species average cell species of the cells in interaction range at each frame of the trajectory, second column gives average of total neighbours per cell, following two columns for species 0 average number of identical and different cell species, vice versa for species 1 in the next two last columns Called by: python neighbour_analysis.py input output input: trajectory file in xyz format output: name of output file get_average_cluster.py : averages number of clusters over given time/frame number Called by : python get_average_cluster.py input output n_or_t t_n_start t_n_end input: Name input file output: Output file name n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end t_n_start: time/line number to start average t_n_end: time/line number to end average. If not given, t_n_start is interpreted, how much time/many line numbers to go back from the end get_average_neighbour.py : averages number of clusters over given time/frame number Called by : python get_average_neighbours.py input output n_or_t t_n_start t_n_end input: Name input file output: Output file name n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end t_n_start: time/line number to start average t_n_end: time/line number to end average. If not given, t_n_start is interpreted, how much time/many line numbers to go back from the end Folder /notebooks/ contains all jupyter notebooks to create the plots, starting from that directory as root directory Folder /src/ contains the source code for the individual simulation setups Folder /plots/ contains all plots created with the jupyter notebooks

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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).
BIP!Citations provided by BIP!
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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