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2,142 results for “by contact”
Assessing-the-role-of-non-linear-contact-mechanics-for-flow-in-fractures---experimental_data
<p>Data to reproduce pressure response spectra from a number of harmonic measurements shown in "Assessing the role of non-linear contact mechanics for<br> flow in fractures"</p> <p><strong>Note:</strong> Data of AFR, BHR and TER has been extracted from papers published by authors others than the ones mentioned in the author list. The publications are referenced in the .txt files and the paper mentioned above.</p>
The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data
<p>In our work, we implemented the ABC-model and could show that one assay for measuring the openness of enhancers is sufficient. Further, we propose a generalised calculation of the ABC-score, which describes enhancer activity in a gene-specific manner, and which includes all TSS, without requiring any additional data. We combined our implementation of the ABC-score with an approach to quantify TF binding affinity into STARE: a framework to derive TF affinities to genes. STARE was also designed for potential application on single-cell data. You can find the code in our <a href="https://github.com/schulzlab/stare">GitHub repository</a> and more details in our <a href="https://doi.org/10.1093%2Fbioinformatics%2Fbtad062">publication</a>.</p> <p>We provide the data for the validation of our ABC-implementation on two CRISPR-screens. We also provide the results of our analysis of single-cell data of the human heart with STARE. All data is in hg19.</p> <p>Content:</p> <ul> <li>CRISPRi_screens: One file for each CRISPRi-screen with interactions that were used to plot precision-recall curves, containing columns for different ABC scoring versions.</li> <li>Enformer: Similar to the CRISPRi_screens, but containing columns for different calculations for Enformer's predicted expression change upon in silico mutagenesis of the enhancer region.</li> <li>K562_CandidateEnhancer: K562 enhancer with the 4th column for enhancer activity, one file for each activity representation that was measured.</li> <li>K562_ABC_Predictions: Regular ABC-scores and generalised ABC-scores for each activity measurement. The files contain all scored interactions for a 10MB window, without any cut-off. We also included the results of the implementation of the ABC-score of Fulco et al. (2019).</li> <li>STARE_Hocker_*: Whole STARE output for human heart single-cell data, one for regular ABC, generalised ABC, generalised ABC with average Hi-C matrix and one based on co-accessibility analysis. All approaches were run with a 5 MB window (except for GeneralisedABC500kb), the ABC-based runs with a score cut-off of 0.02. Each folder contains two subdirectories, one for the ABC-scoring and one for the Gene-TF affinity matrices. The 'ABC_output' also contains a GeneInfo file for each cell type, summarising different attributes per gene.</li> <li>INVOKE_Hocker_*: Folder with the input and output of INVOKE (see https://github.com/schulzlab/tepic), based on the STARE runs. CS genes stands for cell type-specific genes, defined as genes with a z-score across cell types of ≥ 2 and TPM ≥ 0.5. The INVOKE commands were as follows: <ul> <li>Rscript INVOKE.R --dataDir=<TF-Gene matrix> --outDir=<out_path> --response=Expression --regularization=E --performance=TRUE --outerCV=10 --seed=1234</li> </ul> </li> </ul> <p>Importantly, the results are based on data from the following publications:</p> <ul> <li>CRISPRi-screens: <ul> <li>Gasperini, Molly, Andrew J. Hill, José L. McFaline-Figueroa, Beth Martin, Seungsoo Kim, Melissa D. Zhang, Dana Jackson, et al. “A Genome-Wide Framework for Mapping Gene Regulation via Cellular Genetic Screens.” <em>Cell</em> 176, no. 1–2 (January 2019): 377-390.e19. https://doi.org/10.1016/j.cell.2018.11.029.</li> <li> <p>Schraivogel, Daniel, Andreas R. Gschwind, Jennifer H. Milbank, Daniel R. Leonce, Petra Jakob, Lukas Mathur, Jan O. Korbel, Christoph A. Merten, Lars Velten, and Lars M. Steinmetz. “Targeted Perturb-Seq Enables Genome-Scale Genetic Screens in Single Cells.” <em>Nature Methods</em> 17, no. 6 (June 2020): 629–35. https://doi.org/10.1038/s41592-020-0837-5.</p> </li> <li> <p>Fulco, Charles P., Joseph Nasser, Thouis R. Jones, Glen Munson, Drew T. Bergman, Vidya Subramanian, Sharon R. Grossman, et al. “Activity-by-Contact Model of Enhancer–Promoter Regulation from Thousands of CRISPR Perturbations.” <em>Nature Genetics</em> 51, no. 12 (December 2019): 1664–69. https://doi.org/10.1038/s41588-019-0538-0.</p> </li> </ul> </li> <li>Enformer model: Avsec, Žiga, Vikram Agarwal, Daniel Visentin, Joseph R. Ledsam, Agnieszka Grabska-Barwinska, Kyle R. Taylor, Yannis Assael, John Jumper, Pushmeet Kohli, and David R. Kelley. “Effective Gene Expression Prediction from Sequence by Integrating Long-Range Interactions.” <em>Nature Methods</em> 18, no. 10 (October 2021): 1196–1203. https://doi.org/10.1038/s41592-021-01252-x.</li> <li>K562 predictions and average Hi-C matrix: Fulco, Charles P., Joseph Nasser, Thouis R. Jones, Glen Munson, Drew T. Bergman, Vidya Subramanian, Sharon R. Grossman, et al. “Activity-by-Contact Model of Enhancer–Promoter Regulation from Thousands of CRISPR Perturbations.” <em>Nature Genetics</em> 51, no. 12 (December 2019): 1664–69. https://doi.org/10.1038/s41588-019-0538-0.</li> <li>Hi-C matrix for K562 predictions: Rao, S. et al. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell, 159(7), 1665–1680</li> <li>STARE and INVOKE runs: Hocker, J. D. et al. (2021). Cardiac cell type–specific gene regulatory programs and disease risk association. Science Advances, 7(20), eabf1444</li> <li>H3K27ac HiChIP for STARE runs: Anene-Nzelu, C. G. et al. (2020). Assigning Distal Genomic Enhancers to Cardiac Disease–Causing Genes. Circulation, 142(9), 910–912</li> <li>INVOKE software: Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction Schmidt et al., Nucleic Acids Research 2016; doi: 10.1093/nar/gkw1061</li> </ul> <p> </p>
Data set for "The interfacial structure of InP(100) in contact with HCl and H2SO4 studied by reflection anisotropy spectroscopy"
<p>This is the experimental raw data set associated with the following publication: M. Löw, M. Guidat, J. Kim, and MM May, <em>The interfacial structure of InP(100) in contact with HCl and H<sub>2</sub>SO<sub>4</sub> studied by reflection anisotropy spectroscopy</em>, RSC Advances 12 (2022), 32756-32764. <a href="https://doi.org/10.1039/D2RA05159A">DOI:10.1039/D2RA05159A</a></p> <p>The data set is organised along the figures of the publication. '.ers', '.erc', and '.ert' are spectra, colour plots, and transients, respectively, in the native format of Laytec's EpiRAS. '.par' files are in the data format from the Princeton Applied Research VersaSTAT 3F potentiostat. Spectra files containing the name 'Si100' are from Si(100) wafers with native oxide, used for zero-line correction as described in the paper.</p>
IODP Expedition 350 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
IODP Expedition 376 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study
<p>Data and code for publication on <em>Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study</em></p>
Data used in the paper (Two-point optical manipulation reveals mechanosensitive remodeling of cell-cell contacts in vivo)
<p>Data used in the paper (Two-point optical manipulation reveals mechanosensitive remodeling of cell-cell contacts in vivo)</p>
Dataset related to publication "Non-contact thermometer for improved air temperature measurements"
<p>These datasets were used to produce Fig. 6, 8 and 9 in paper "Non-contact thermometer for improved air temperature measurements" to be published in <em>Sensors </em><strong>2023</strong><em>, 23. </em>The data were produced within the EMPIR project 18SIB01 GeoMetre.</p>
IODP Expedition 385 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Contact data of older adults (70+) in the Netherlands in 2021
<p>SCONE (Studying CONtacts of Elderly): Contact data of frail and non-frail older adults (70+) collected in the Netherlands during two survey periods in 2021</p>
Data sets for heat generation and associated contact temperature during an oblique impact of a deformable particle and a rigid substrate
<p>This dataset contains essential data from the Finite Element Method model predicting heat generation due to friction and plastic deformation during the oblique impact of a deformable particle and a rigid substrate. Part of this data was processed and published in a journal article (<a href="https://doi.org/10.1016/j.powtec.2023.118481">https://doi.org/10.1016/j.powtec.2023.118481</a>). The following is the description of the data files and the associated Figure in the original paper.</p> <p>‘Heat_Elast_Vt.xlsx’ and ‘Temp_Elast_Vt.xlsx’ data for the evolution of heat and nodal contact temperature, respectively, for varying tangential velocity. Data was used in Figs. 7a and 7b in the associated paper</p> <p>‘Heat_Vt.xlsx’ and Heat_Vn.xlsx’ data for the evolution of heat for various tangential velocities and normal velocities, respectively. Data was used in Figs. 8a and 8b in the associated paper.</p> <p>‘Heat_YM.xlsx’ and ‘Temp_YM.xlsx’ data for the evolution of heat and nodal contact temperatures, respectively, for varying Young’s moduli. Data was used in Figs. 9 and 10 in the associated paper.</p> <p>‘Heat_YS.xlsx’ and ‘Temp_YS.xlsx’ data for the evolution of heat and nodal contact temperatures for varying yield strengths. Data was used in Figs. 11 and 12 in the associated paper.</p> <p>‘Heat_Den.xlsx’ and ‘Temp_Den.xlsx’ data for heat and nodal contact temperature evolution, respectively, for varying yield strengths. Data was used in Figs. 13 and 14 in the associated paper.</p> <p> ‘Temp_TC.xlsx’ data for the evolution of nodal contact temperatures for varying thermal conductivities. Data was used in Fig. 15 in the associated paper.</p> <p>‘Temp_HC.xlsx’ data for the evolution of nodal contact temperatures for varying specific heat capacities. Data was used in Fig. 16 in the associated paper.</p>
IODP Expedition 396 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
IODP Expedition 354 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Data sets for temperature rise due to frictional heat generation during a sliding contact between an elastic particle and a rigid substrate
<p>This dataset contains essential data from the Finite Element Method model predicting heat generation due to friction during the sliding contact between an elastic particle and a rigid substrate. Part of this data was processed and presented in an article under review for journal publication. The following is the description of the data files and the associated Figure in the original paper.</p> <p>'Temp_CoeffFric_01_055.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various friction coefficient values (0.1-0.55).</p> <p>'Temp_Load_001_01.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various normal load values (0.01-0.1 N).</p> <p>'Temp_Vel_02_1.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various sliding velocity values (0.2-1 m/s).</p> <p>'Temp_TC_5_100.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various thermal conductivity values. (i.e. 5-100 W/m K).</p> <p>'Temp_HC_100_1600.xlsx' data for temperature evolution for the nodes in the contacts and along the particle radius for various thermal conductivity values. (i.e. 100-1600 J/kg K).</p> <p> </p>
Dataset of the Journal article "Energy duty in direct contact membrane distillation of hypersaline brines operating at the water-energy nexus"
<p>This repository contains the Dataset of the Journal article "Energy duty in direct contact membrane distillation of hypersaline brines<br> operating at the water-energy nexus" published on Journal of Membrane Science. </p>
Data repository for manuscript "Contacting individual graphene nanoribbons using carbon nanotube electrodes"
<p>This is the raw data for the manuscript "Contacting individual graphene nanoribbons using carbon nanotube electrodes”.</p>
IODP Expedition 369 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
Equilibrium contact angle of acqueous glycerol on a silica-like surface from Molecular Dynamics
<p>This dataset contains the results of Molecular Dynamics simulations of quasi-2D water-glycerol liquid droplets, spreading on silica-like surfaces. The goal of the simulations is to quantify the equilibrium contact angle of said droplets.</p> <p>The pattern "Glycerol***" refers to the mass fraction of glycerol ("000": pure water, "100": pure glycerol). Each folder contains configuration files and compressed output molecular trajectories. The contact angle is computed from density maps binned on-the-fly using a customized Gromacs version (<a href="https://github.com/pjohansson/gromacs-flow-field">https://github.com/pjohansson/gromacs-flow-field</a>); frames are placed in a tarball ("flow-***p.tar.gz").</p> <p>The zipped folder 'scripts.zip' contains a self-contained library of functions to read density maps and a Jupyter notebook with an example of density reading and plotting.</p> <p>Simulations are performed with Gromacs. We refer to the code documentation for further information (<a href="https://manual.gromacs.org/">https://manual.gromacs.org/</a>).</p>
Source height and contact with terrestrial soil drive transplanted epiphyte performance
<ol> <li class="MsoNormal">Epiphytes are characterized by their ability to survive without a root connection to the ground, but many basic life-history traits and ecological trade-offs of this unique aerial growth habit remain largely uncharacterized. Mortality causes are still not well understood, but falling from the host tree has been suggested as a leading cause of epiphyte mortality and community dynamics. Little empirical evidence exists for <em>why</em> epiphytes do not survive when forced to become terrestrial, and few studies exist that transplant epiphytes between high- and low-forest strata to test trade-offs between thriving in canopy environments and survival in the forest understory.</li> <li class="MsoNormal">Here, we experimentally test two hypotheses regarding the drivers of epiphyte mortality in a cloud forest of central Panama. We test whether simple contact with terrestrial soil is deleterious to epiphytes, preliminarily testing the Epiphyte Enemy Escape Hypothesis, and test the Vertical Niche Differentiation Hypothesis, wherein epiphytes are specifically adapted for microsites throughout the vertical forest strata. By monitoring survival, leaf loss, and health status of 270 transplanted epiphytes for a year and a half, we pinpoint the extent to which soil contact and height of origin regulate epiphyte performance. </li> <li class="MsoNormal">We found that contact with terrestrial soil itself was detrimental to epiphytes <em>in situ</em>, providing some of the first empirical data to explain why falling onto the ground, versus falling into the understory, is particularly fatal to epiphytes. However, we also found that mortality rates vary substantially among taxonomic groups and among epiphytes that originally came from different height strata.</li> <li class="MsoNormal"> <strong>Synthesis.</strong> Plants that are adapted for the canopy experience a trade-off with higher mortality when in contact with terrestrial soil. Follow-up studies should explore the role of terrestrial soil microbes and physiological constraints as potential drivers of decreased grounded epiphyte survival. </li> </ol>
IODP Expedition 382 Magnetic susceptibility (point or contact system)
<p>Magnetic susceptibility was measured on section halves on the Section Half Multisensor Logger (SHMSL) using a Bartington MS2 meter and either a MS2E or MS2K probe. Because all JRSO cores meet minimum size requirements for these two probes, MSPOINT data are corrected for volume and recorded in SI susceptibility units (x10<sup>-5</sup>).</p>
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Allen Brain Atlas
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OpenNeuro
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