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153
datasets available to search
ShareScore release 0.9.0
Dataset results
153 results for “Tissue mechanics”
Hyaluronic acid networks and emergent tissue mechanics orchestrate mammalian limb regeneration
GEO Series GSE274858. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
Molecular mechanisms in lung tissue of yak provide insights into high-altitude adaptation by transcriptome-wide analysis
GEO Series GSE153963. Bos grunniens; Bos taurus. 22 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Modulation of immune response and tissue repair mechanisms in the gill filaments of Atlantic salmon (Salmo salar) affected by complex gill disease (CGD) in a marine open sea-cage environment
GEO Series GSE293344. Salmo salar. 9 samples. Type: Expression profiling by high throughput sequencing.
Abundant small RNAs in the reproductive tissues of the honey bee, Apis mellifera, are a plausible mechanism for epigenetic inheritance and parental manipulation of gene expression
GEO Series GSE182720. Apis mellifera. 24 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Interferon-alpha mediates the development of autoimmunity by direct tissue toxicity and through immune-cell recruitment mechanisms
GEO Series GSE25115. Homo sapiens; Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
A transcriptional atlas of early Arabidopsis seed development suggests mechanisms for inter-tissue coordination
GEO Series GSE295007. Arabidopsis thaliana. 7 samples. Type: Expression profiling by high throughput sequencing.
Hedgehog targets in the Drosophila embryo and the mechanisms that generate tissue-specific outputs of Hedgehog signaling
GEO Series GSE24055. Drosophila melanogaster. 20 samples. Type: Genome binding/occupancy profiling by genome tiling array; Expression profiling by array.
HsfA2 controls the activity of developmentally and stress-regulated heat stress protection mechanisms in tomato male reproductive tissues
GEO Series GSE68500. Solanum lycopersicum. 8 samples. Type: Expression profiling by high throughput sequencing.
Molecular mechanisms in lung tissue of yak provide insights into high-altitude adaptation by transcriptome-wide analysis [miRNA-seq]
GEO Series GSE153962. Bos grunniens; Bos taurus. 11 samples. Type: Non-coding RNA profiling by high throughput sequencing.
An RNA polymerase III tissue and tumor atlas uncovers context-specific activities linked to 3D epigenome regulatory mechanisms
GEO Series GSE306294. Homo sapiens. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Cell-type-specific RNA Pol II activity maps in intact-tissues: gateway to mammalian gene regulatory mechanisms in vivo [RNA-seq]
GEO Series GSE278913. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Biological Aging and Circadian Mechanisms in Murine Brown Adipose Tissue, Inguinal White Adipose Tissue, and Liver (Nov 2009 dataset)
GEO Series GSE25323. Mus musculus. 36 samples. Type: Expression profiling by array.
Combination with ERR gamma agonist and mechanical stretching enhances maturation of 3D cardiac tissue and manifests the hypertrophic cardiomyopathy phenotype
GEO Series GSE203102. Homo sapiens. 21 samples. Type: Expression profiling by high throughput sequencing.
A single-cell atlas of bovine skeletal muscle tissue reveals mechanisms underlying differences in quality between Wagyu and Brahman beef.
GEO Series GSE205347. Bos taurus. 6 samples. Type: Expression profiling by high throughput sequencing.
Study of the pathology and the underlying molecular mechanism of tissue injury around hematoma following intracerebral hemorrhage
GEO Series GSE171144. Rattus norvegicus. 6 samples. Type: Expression profiling by array.
Macrophages sense ECM mechanics and growth factor availability through cytoskeletal remodeling to regulate their tissue repair program [ATAC-seq]
GEO Series GSE238262. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Transcriptome analyses of the cortex and white matter of focal cortical dysplasia type II human samples: novel insights into disease mechanisms and contributions to tissue characterization
GEO Series GSE213488. Homo sapiens. 35 samples. Type: Expression profiling by high throughput sequencing.
Data for: Tissue evolution: Mechanical interplay of adhesion, pressure, and heterogeneity
<p>Tissue evolution: mechanical interplay of adhesion, pressure, and heterogeneity</p> <p>Full Data for corresponding publication.</p> <p> </p> <p>All folders are named by the actual simulation values used, not by the rescaled values shown in the paper<br> All folders contain data files, trajectory files are converted and zipped, as well as the executable and the starting configuration file.<br> Start simulations with ./cell_dpd starting_configuration.sconf</p> <p>The simulation for Fig.1 can be found in folder /free_evolution/<br> 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.</p> <p>The simulation for Fig.2 and Fig.S3 can be found in folder /heterogeneity/sharp_treshold/<br> folder structure: /heterogeneity/sharp_treshold/pm/tradeoff/ with mutation probability pm and tradeoff parameter between changes in G and F1.</p> <p>The simulation for Fig.S1 can be found in folder /heterogeneity/division_rate/tradeoff/ with tradeoff parameter between changes in G and F1.</p> <p>The simulation for the division rate simulations of Fig.S2 can be found in folder /pair_competition/12x12x12/40_6.0/division_rate/</p> <p>The simulation for Figs. 4, 5 and S4 can be found in folder /pair_competition/12x12x12/40_6.0/sharp_treshold/<br> 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).</p> <p>The simulations for Fig.6 can be found in folder /mutationrate/<br> 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.</p> <p>The simulations for Fig.7 can be found in folder /survival/<br> 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).</p> <p>The simulation for Fig.S5 can be found in folder /unstable/<br> 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</p> <p>Folder /scripts/ contains all scripts to analyze the simulation results, described in the following:</p> <p>get_phi.py : Outputs file with cell number fractions from input file containing absolute cell numbers.<br> Called by : python get_phi.py input output<br> input: Name input file (in all simulations numcells.dat)<br> output: Name output file</p> <p>minimize_uid: Outputs minimized trajectory file as input.min<br> Called by: ./minimize_uid input<br> input: name trajectory file (in all simulations traj.dat)</p> <p>convert2xyz_spec: Outputs trajectory in xyz format as input.xyz for pair competitions with n=2<br> Called by : ./convert2xyz_spec input<br> input: name trajectory file (minimized file from minimize_uid)</p> <p>convert2xyz_new: Outputs trajectory in xyz format as input.xyz for heterogeneity simulations for n=21 species<br> Called by : ./convert2xyz_new input<br> input: name trajectory file (minimized file from minimize_uid)</p> <p>block_average.py : Outputs file with block averaged value from input file.<br> Called by : python block_average.py input output column n_or_t t_n_start t_n_end<br> input: Name input file<br> output: Output file name<br> column: column to be averaged<br> n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end<br> t_n_start: time/line number to start average<br> 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</p> <p>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<br> Called by: python cluster_analysis.py input output<br> input: trajectory file in xyz format<br> output: name of output file</p> <p>neighbour_analysis.py : Analysis of the cell species average cell species of the cells in interaction range at each frame of the trajectory,<br> second column gives average of total neighbours per cell, following two columns for species 0 average number of identical <br> and different cell species, vice versa for species 1 in the next two last columns<br> Called by: python neighbour_analysis.py input output<br> input: trajectory file in xyz format<br> output: name of output file</p> <p>get_average_cluster.py : averages number of clusters over given time/frame number<br> Called by : python get_average_cluster.py input output n_or_t t_n_start t_n_end<br> input: Name input file<br> output: Output file name<br> n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end<br> t_n_start: time/line number to start average<br> 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<br> get_average_neighbour.py : averages number of clusters over given time/frame number<br> Called by : python get_average_neighbours.py input output n_or_t t_n_start t_n_end<br> input: Name input file<br> output: Output file name<br> n_or_t: If 0, interprete following arguments as time, else as line numbers to start/end<br> t_n_start: time/line number to start average<br> 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</p> <p><br> Folder /notebooks/ contains all jupyter notebooks to create the plots, starting from that directory as root directory</p> <p>Folder /src/ contains the source code for the individual simulation setups</p> <p>Folder /plots/ contains all plots created with the jupyter notebooks</p>
Characterization of Mechanical Tissue Properties in Patients With Pancreatic, Liver, or Colon Cancer
ClinicalTrials.gov study NCT03137706. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Mechanisms of Tissue Repair After Muscle Injury and Tendon Strain
ClinicalTrials.gov study NCT05809947. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.