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3,878 results for “Molecular data”
Data for: Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network
<p>The data is supplementary to the publication "Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network", DOI: <a title="DOI URL" href="https://doi.org/10.1021/acs.jpclett.4c00406">10.1021/acs.jpclett.4c00406</a></p> <p>Key words: Thermal volume expansion, Interphase dynamics, Temperature-modulated optical refractometry, Nanoparticles, Optical Remanence, Hysteresis, Refractive index</p> <p>The data sets contain measured and processed data on the interphase dynamics of a nanoparticle modified epoxy resin collected via Temperature-modulated optical refractometry (TMOR).</p> <p>Material details:</p> <ul> <li>Cycloaliphatic epoxy resin + Anhydride curing agent + 1-methylimidazole</li> <li>Core-shell rubber nanoparticles, 100 nm, dispersed in a cycloaliphatic epoxy carrier resin</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629.</li> </ul>
Data of publication Ultra-narrow Optical Linewidths in Rare-Earth Molecular Crystals
<p>Data corresponding to main text Figures, Extended Data figures, and Supplementary Figures in publication 'Ultra-narrow Optical Linewidths in Rare-Earth Molecular Crystals, by D. Serrano, S. Kumar Kuppusamy, B. Heinrich, O. Fuhr, M. Ruben and P. Goldner.</p>
Morphometric data from: Incongruent molecular and morphological variation in the crab spider Synema globosum (Araneae: Thomisidae) in Europe
<p>Here we provide the complete set of files used by <a href="https://doi.org/10.3897/zookeys.1078.64116">Urfer et al. (2021</a>, see References section below for the complete citation of the publication) for the morphometric and the molecular analysis. In particular, we provide the following documents:</p> <p><br> PART 1: MORPHOMETRIC ANALYSIS</p> <p>- 1_Synema_data_multiple_imputation_mice.R: R-script used for replacing NAs.</p> <p>- 1_Synema_data_NA_imputed.csv: Dataset with raw values (in millimeters) of all 28 specimens used for the morphometric analysis. Each specimen was measured 4 times. NAs replaced using the R-script "Synema_multiple_imputation_mice.R" above. This is the datafile used for all morphometric analyses.</p> <p>- 1_Synema_data_with_NA.csv: Dataset with raw values (in millimeters) of all 28 specimens. Each specimen was measured 4 times. NAs not replaced.<br> <br> - 1_Synema_Reliability.R: R-script for calculating reliability.<br> <br> - 1_Synema_Reliability_supplementary_figure.pdf: Results of reliability analysis presented in a bar plot.</p> <p>- 1_Synema_Reliability_supplementary_table.txt: Results of reliability analysis presented in a table.<br> <br> - 1_Synema_Shape_PCA_and_PCA_Ratio_Spectrum.R: R-script for calculating the shape PCA and the PCA Ratio Spectrum of the first shape PC. You may get the necessary MRA source script from http://doi.org/10.5281/zenodo.4250142<br> <br> - Synema_globosum_AR9379_PV.jpg, Synema_globosum_AR9379_PV.jpg, Synema_globosum_AR9379_PV.jpg, etc.: Photographs taken with a LEICA M205 C stere-omicroscope.</p> <p> 1. Numbers after AR_ refer to the inventory number of the specimens in the Natural History Musuem Bern (NMBE). The specimen number was also used in the data file.<br> 2. The photo named "Synema_globosum_AR9163_with_measurements" shows the position of the measurements. Otherwise, the measurements are not indicated in the raw photos.</p> <p><br> Example image Character name Definition<br> Synema_globosum_AR9163_with_measurements cym.l Cymbium lenght Distance of the anterior margin to the tip of the cymbium<br> Synema_globosum_AR9163_with_measurements cym.b Cymbium breadth widest breadth of the cymbium<br> Synema_globosum_AR9163_with_measurements bul.b Bulb breadth widest breadth of the genital bulbus<br> Synema_globosum_AR9163_with_measurements tib.b Tibia breadth breadth of the tibia base at the patella joint</p>
The Data Related to Interfacial Shift Keying Allows a High Information Rate in Molecular Communication
<p>This dataset is related to a method for molecular communication in fluids described on "Fluorescent nanoparticles for reliable communication among implantable medical devices," Carbon, vol. 190, pp. 262-275, Apr. 2022, by Federico Calì, Luca Fichera, Giuseppe Trusso Sfrazzetto, Giuseppe Nicotra, Gianfranco Sfuncia, Elena Bruno, Luca Lanzanò, Ignazio Barbagallo, Giovanni Li-Destri, Nunzio Tuccitto; doi: 10.1016/J.CARBON.2022.01.016. <br> The dataset is linked to the manuscript entitled "Interfacial Shift Keying Allows a High Information Rate in Molecular Communication: Methods and Data" by F. Calì, G. Li-Destri, and N. Tuccitto submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (T-MBMC).<br> The data, including elapsed time (s), starting from the injection and fluorescence intensity (a.u.), is given in tab-separated values format as .txt files. When present, a column includes the intensity subtracted for the baseline and the subtracted and normalized intensity. In all cases, the baseline was obtained by performing a linear fit between 10 and 110 s and subtracting the line obtained from the entire dataset.<br> </p>
Supplementary data: Agro-morphological and molecular characterization reveal deep insights in promising genetic diversity and marker-trait associations in Fagopyrum esculentum and F. tataricum
<p>Our study focuses on the global/European buckwheat germplasm collected as part of the ECOBREDD project. The potential of this highly diverse collection for organic buckwheat breeding was evaluated at two complementary levels: phenotypic and genetic. Here, we characterized the phenotypic and genetic diversity of a global collection of the two cultivated buckwheat species <em>Fagopyrum esculentum</em> and <em>F. tataricum</em> (190 and 51 accessions, respectively) using 37 agro-morphological traits and 24 SSR markers (Simple Sequence Repeats) (see publication and info sheet of the data).</p>
MCR LTER: Coral Reef: Distinguishing the molecular diversity, nutrient content, and energetic potential of exometabolomes produced by macroalgae and reef-building corals; data for Kelly et al., 2022 PNAS
Metabolites exuded by primary producers comprise a significant fraction of marine dissolved organic matter, a poorly characterized, heterogenous mixture that dictates microbial metabolism and biogeochemical cycling. We present a foundational untargeted molecular analysis of exudates released by coral reef primary producers using liquid chromatography–tandem mass spectrometry to examine compounds produced by two coral species and three types of algae (macroalgae, turfing microalgae, and crustose coralline algae [CCA]) from Mo’orea, French Polynesia. Of 10,568 distinct ion features recovered from reef and mesocosm waters, 1,667 were exuded by producers; the majority (86%) were organism specific, reflecting a clear divide between coral and algal exometabolomes. These data allowed us to examine two tenets of coral reef ecology at the molecular level. First, stoichiometric analyses show a significantly reduced nominal carbon oxidation state of algal exometabolites than coral exometabolites, illustrating one ecological mechanism by which algal phase shifts engender fundamental changes in the biogeochemistry of reef biomes. Second, coral and algal exometabolomes were differentially enriched in organic macronutrients, revealing a mechanism for reef nutrient-recycling. Coral exometabolomes were enriched in diverse sources of nitrogen and phosphorus, including tyrosine derivatives, oleoyl-taurines, and acyl carnitines. Exometabolites of CCA and turf algae were significantly enriched in nitrogen with distinct signals from polyketide macrolactams and alkaloids, respectively. Macroalgal exometabolomes were dominated by nonnitrogenous compounds, including diverse prenol lipids and steroids. This study provides molecular-level insights into biogeochemical cycling on coral reefs and illustrates how changing benthic cover on reefs influences reef water chemistry with implications for microbial metabolism. This material is based upon work supported by the U.S. National Science Founda
Data from: "Rapid molecular evolution of Spiroplasma symbionts of Drosophila"
<p>This repository contains data and information to reproduce the findings reported in the paper.</p> <p>File descriptions:</p> <ul> <li>OTU_sequences.fasta – all <em>Spiroplasma</em> sequences that contained an <a href="https://pfam.xfam.org/family/OTU">OTU domain</a> as predicted by <a href="https://www.ebi.ac.uk/Tools/pfa/pfamscan/">PfamScan</a></li> <li>OTU_alignments.fasta – alignment of OTU domains performed using <a href="https://mafft.cbrc.jp/alignment/software/">Mafft</a></li> <li>RIP_sequences.fasta – all <em>Spiroplasma</em> sequences that contained an <a href="https://pfam.xfam.org/family/RIP">RIP domain</a> as predicted by <a href="https://www.ebi.ac.uk/Tools/pfa/pfamscan/">PfamScan</a></li> <li>RIP_alignments.fasta – alignment of RIP domains performed using the <a href="http://hmmer.org/">HMMER package</a></li> <li>Spiroplasma_supermatrix.fasta – Fasta alignment of concatenated single copy <em>Spiroplasma</em> loci conserved across the investigated strains. Loci that showed signs of recombination were not included</li> <li>Spiroplasma_partitions.txt – Lists the loci that make up the <em>Spiroplasma</em> supermatrix</li> <li>Spiroplasma_partitioning.scheme.txt – Partitioning scheme employed in our Maximum Likelihood analysis of the supermatrix. This was the best fitting partitioning scheme as determined with <a href="http://www.iqtree.org/">IQ-TREE</a></li> <li>Protocol_1.pdf – Chloroform–Ethanol protocol used for extracting <em>Spiroplasma</em> DNA for <em>s</em>Hy-Tx</li> </ul>
A dissymmetric [Gd2] coordination molecular dimer hosting six addressable spin qubits. Open data sets
<p>Includes data relevant for publication with DOI <a href="https://doi.org/10.1038/s42004-020-00422-w">10.1038/s42004-020-00422-w</a> plus a table with information about how the data were obtained and processed.</p>
An intense, cold, velocity-controlled molecular beam by frequency-chirped laser slowing - supporting data
<p>These are the data presented in figures 3, 4, 5, 6 and 7 of our paper "An intense, cold, velocity-controlled molecular beam by frequency-chirped laser slowing". The first line of each data file explains the content. The second line labels the columns. The remaining rows give the data.</p>
Strongly Enhanced Cooperative Surface Propensity of Atmospherically Relevant Organic Molecular Ions in Aqueous Solution - data
<p>Dataset pertaining to the manuscript "Boosting aerosol surface effects: strongly enhanced cooperative surface propensity of atmospherically relevant organic molecular ions in aqueous solution", published in <a href="https://doi.org/10.5194/acp-25-3503-2025">Atmos. Chem. Phys., 25, 3503–3518, 2025</a>. Using liquid-jet photoelectron spectroscopy, we investigate the surface propensity of various carbonaceous species in aqueous solution. We cover a range of substances relevant to atmospheric climate models. Here we give the data of Fig.s 1-3 of our manuscript in numeric form, and document the underlying photoemission spectra including all relevant metadata.</p> <p>Experimental data are documented in the NeXus format (extension .nxs). For a description see:<br>The NeXus Data Format definition (v2024.02), https://manual.nexusformat.org/index.html<br>NXmpes expansion for FAIRmat data (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/classes/contributed_definitions/NXmpes.html<br>NXmpes_liquid expansion to NXmpes (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/mpes-liquid/classes/contributed_definitions/NXmpes_liquid.html</p> <p>The following files are provided:<br>'Data Collection_Core.nxs' - Photoemission data, core level spectra<br>'Data Collection_Valence.nxs'<strong> </strong> - Photoemission data, valence spectra</p> <p>Ascii data of figures 1a, 2 and 3:<br>'Figure 1 data.txt'<br>'Figure 2 data.txt'<br>'Figure 3 data.txt'</p> <p>Contact person for questions regarding this data set: Uwe Hergenhahn, uhe@fhi.mpg.de . If you use these data for your scientific work we kindly ask you to send us a copy of your published results.</p> <p>Acknowledgements: We acknowledge DESY (Hamburg, Germany), a member of the Helmholtz Association HGF, for the provision of experimental facilities. Parts of this research were carried out at PETRA III, and we would like to thank Moritz Hoesch and his team for assistance in using beamline P04. Beamtime was allocated for proposal I-20220937 EC. Harmanjot Kaur and Bernd Winter acknowledge the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 883759, AQUACHIRAL). Stephan Thürmer acknowledges support from JSPS KAKENHI (grant no. JP20K15229) and ISHIZUE 2024 of Kyoto University. Florian Trinter acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project 509471550, Emmy Noether Programme. Florian Trinter and Bernd Winter acknowledge support by the MaxWater initiative of the Max-Planck-Gesellschaft. Olle Björneholm acknowledges support from the Swedish Research Council (VR) through project 2023-04346 and the Swedish Foundation for International Cooperation in Research and Higher Education (STINT) through project 202100-2932. Ricardo Marinho, Joel Pinheiro, and Arnaldo Naves de Brito acknowledge support from the Swedish–Brazilian collaboration STINT-CAPES (process no. 88881.465527/2019-01). Arnaldo Naves de Brito acknowledges support from FAPESP (the São Paulo Research Foundation, process no. 2017/11986-5), Shell and ANP (Brazil’s National Oil, Natural Gas and Biofuels Agency), and CNPq-Brazil (process no. 401581/2016-0). Harmanjot Kaur and Shirin Gholami acknowledge support by the IMPRS for Elementary Processes in Physical Chemistry.</p> <p>Financial support: This research has been supported by the European Research Council, Horizon Europe (grant no. 883759); the Japan Society for the Promotion of Science (grant no. JP20K15229); the Deutsche Forschungsgemeinschaft (grant no. 509471550); the Vetenskapsrådet (grant no. 2023-04346), the Swedish Foundation for International Cooperation in Research and Higher Education (grant no. 202100-2932); the Fundação de Amparo à Pesquisa do Estado de São Paulo (grant no. 2017/11986- 5); and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (grant no. 401581/2016-0).</p> <p>Version history:<br>1 - initial release<br>2 - numbering of figures adapted to published version, photoemission data added.</p>
Supporting Data - Taxonomic reassessment of Tetrapygus niger (Arbacioida, Echinoidea): molecular and morphological evidence support its placement in Arbacia
<p>This dataset contains the accession numbers and links of the sequences of the specimens analyzed by this work, other sequences used for the analyses can be found in the original article. The species from which the sequences were extracted are: Tetrapygus niger Molina, 1782; Arbacia dufresnii Blainville, 1825; Arbacia spatuligera Valenciennes, 1846 and Coelopleurus floridanus A. Agassiz, 1872. The accession numbers for the Cytochrome Oxidase subunit I (COI) and 28S of the nuclear genome are presented separately.</p><p>In addition, the morphological data of Tetrapygus niger (Test diameter, test height and peristome diameter) presented in this study are shown, as well as their collectors, corresponding collection, country and locality.</p>
Data for "A Quantum Definition of Molecular Structure"
<p>Supplemental data for our article "A Quantum Definition of Molecular Structure".</p><p>Version 1.1.0 contains data for additional k-medoids runs performed on different subsets of the complete sample.</p>
Data for the publication "Sodium Triflate Water-in-Salt Electrolyte in Advanced Battery Applications: A First-principles Based Molecular Dynamics Study"
<p>The datasets 'CONTCAR_aiMLMD' and 'CONTCAR_AIMD' represent the final structures obtained from the aiMLMD and AIMD simulations, respectively. These simulations were conducted using VASP at T=333K and c=9.25 m.</p> <p>The datasets 'NP.rdf' and 'MSD_NP.xlsx' represent the radial pair distribution functions at different time steps and the time-dependent variations of mean squared displacement for sodium in 10 segments of the classical MD trajectory. The associated MD simulation was performed using a nonpolarizable force field in the LAMMPS package at T=333K and c=9.25 m. The file 'dataNP.lmp' includes the initial configuration for this simulation. The GROMOS parameters were employed for LJ interactions of sodium and all other force field parameters were set according to Table 1 in the manuscript.</p> <p>The datasets 'P.rdf' and 'MSD_P.xlsx,' respectively, represent the radial pair distribution functions at different time steps and the time-dependent variations of mean squared displacement for sodium in 10 segments of the classical MD trajectory. These data were obtained employing the Drude oscillator model in the LAMMPS package at T=333K and c=10 m. The file 'dataP.lmp' includes the initial configuration for this simulation. The simulation was conducted using the optimal force field parameters 'Sys. 1,' as described in table 3 of the manuscript.</p> <p>The second column in the files 'NP.rdf' and 'NP.rdf' represents the distance from sodium. The subsequent odd columns display the radial distribution functions for the Na-C, Na-F, Na-S, Na-O, Na-Na, Na-Hw, and Na-Ow pairs, while the even columns present the coordination numbers for the same atom pairs.</p>
Data related to the article "Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes"
<p>Contains input files and data used to generate the figures of the article:</p> <p>Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes<br>(Giovanni Pireddu, Connie J. Fairchild, Samuel P. Niblett, Stephen J. Cox and Benjamin Rotenberg)</p> <p>ChemRxiv: https://doi.org/10.26434/chemrxiv-2023-2ccrw</p> <p>Published version: to be inserted upon publication</p> <p>The folder EXAMPLE_INPUT_FILES contains typical [MetalWalls](https://doi.org/10.21105/joss.02373) ([repository](https://gitlab.com/ampere2/metalwalls)) and [LAMMPS]([repository](https://github.com/lammps/lammps)) input files used to perform the molecular simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper (see below).</p> <p><br>Notes: <br>1) In the file names, the notation 'M01', 'M05', 'M10' and 'M15' refers to the salt concentration in each system (0.1, 0.5, 1.0 and 1.5, respectively). 'W' refers to pure water (0 M) systems.<br>2) In the file names, the notation 'd1', 'd2', 'd3', 'd4', refers to different interelectrode distances (d1= 2.56 nm; d2= 5.07 nm; d3= 9.80 nm; d4= 19.84 nm) <br>3) The files containing the polarization cross-correlation are marked with 'AxB' indicating the cross-correlation between the contributions A and B. Specifically A and B can be: <br> - T = total<br> - I = ion<br> - W = water</p> <p><br>Figure 1:<br>- Panel B<br> - 'Fig1_CapConcentration': Differential capacitance scaled by electrode area as a function of NaCl concentration<br>- Panel C<br> - 'Fig1_QACF_*': Electrode charge autocorrelation function<br>- Panel D<br> - 'Fig1_Norm_QACF_*': Normalized electrode charge autocorrelation function<br> - 'Fig1_NormChar_*': Normalized non-equilibrium charge response</p> <p>Figure 2:<br>- Panel A: <br> - 'Fig2_ReZ_*': Real part of impedance<br>- Panel B:<br> - 'Fig2_nImZ_*': Negative imaginary part of impedance<br>- Panel C:<br> - 'Fig2_ReZint_*': Real part of interfacial impedance<br> - 'Fig2_Resistivities.dat': Resistivity as a function of NaCl concentration (bulk, confined, Nernst-Einstein)<br>- Panel D:<br> - 'Fig2_nImZint_*': Negative imaginary part of interfacial impedance<br> - 'Fig2_ECM*': Capacitor contributions to the imaginary part of interfacial impedance (finite concentrations)<br> - 'Fig2_ECW1.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Full cell capacitance taken into account<br> - 'Fig2_ECW2.dat': Capacitor contributions to the imaginary part of interfacial impedance (pure water). Interfacial capacitance taken into account </p> <p>Figure 3:<br>- Panel A:<br> - 'Fig3_ReCond_Peyman_M10.dat': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br> - 'Fig3_ReCond_Querry_M10.dat': Real part of conductivity (data from: MR Querry, RC Waring, WE Holland, GM Hale, W Nijm, Optical Constants in the Infrared for Aqueous Solutions of NaClt. J. Opt. Soc. Am. 62 (1972)) <br> - 'Fig3_ReCond_Vinh_M10.dat': Real part of conductivity (data from: NQ Vinh, et al., High-precision gigahertz-to-terahertz spectroscopy of aqueous salt solutions as a probe of the femtosecond-to-picosecond dynamics of liquid water. The J.<br>Chem. Phys. 142, 164502 (2015).)<br> - 'Fig3_ReCond_M10.dat': Real part of conductivity from MD simulations<br>- Panel B:<br> - 'Fig3_ReCond_M*/W.dat': Real part of conductivity from MD simulations<br> - 'Fig3_ReCond_Peyman_M*': Real part of conductivity (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))<br>- Panel C:<br> - 'Fig3_Cond0.dat': Static conductivity as a function of concentration (MD data)<br> - 'Fig3_Cond0_Buchner.dat': Static conductivity as a function of concentration (data from: R Buchner, GT Hefter, PM May, Dielectric relaxation of aqueous nacl solutions. The J. Phys. Chem. A 103, 1–9 (1999))<br> - 'Fig3_Cond0_Peyman.dat': Static conductivity as a function of concentration (data from: A Peyman, C Gabriel, E Grant, Complex permittivity of sodium chloride solutions at microwave frequencies. Bioelectromagnetics 28, 264–274 (2007))</p> <p>Figure 4:<br>- Panel A: <br> - 'Fig4_ReZ_d*': Real part of impedance (MD simulations)<br> - 'Fig4_ReZEC_d*': Real part of impedance (equivalent circuit model)<br>- Panel B:<br> - 'Fig4_nImZ_d*': Negative imaginary part of impedance (MD simulations)<br> - 'Fig4_nImZEC_d*': Negative imaginary part of impedance (equivalent circuit model)</p> <p>Figure 5:<br>- 'Fig5_TauQ.dat': timescales from the total charge autocorrelation functions<br>- 'Fig5_iontot.dat': timescales from the TxI autocorrelation function<br>- 'Fig5_RC.dat': timescales from the RC estimates<br>- 'Fig5_RbulkC.dat': timescales from the RbulkC estimates<br>- 'Fig5_Taudiff.dat': timescales from the difference between electrolyte and pure water QACFs<br>- 'Fig5_taud.dat': tau_d analytical timescales<br>- 'Fig5_tauDebye.dat': tau_Debye analytical timescales<br>- 'Fig5_taumix.dat': tau_mix analytical timescales</p> <p>Figure 6:<br>- Panel A:<br> - 'Fig6_Static_*: Static correlation between polarization contributions as a function of salt concentration<br>- Panel B:<br> - 'Fig6_Dynamic_EQ_*_M01' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M01' Dynamical correlations between polarization contributions (non-equilibrium MD results)<br>- Panel C:<br> - 'Fig6_Dynamic_EQ_*_M10' Dynamical correlations between polarization contributions (equilibrium MD results)<br> - 'Fig6_Dynamic_NEQ_*_M10' Dynamical correlations between polarization contributions (non-equilibrium MD results)</p> <p> </p> <p> </p>
Data for "Dynamic of binary molecular systems – advantages and limitations of NMR relaxometry"
<p>Raw data for "Dynamic of binary molecular systems – advantages and limitations of NMR relaxometry". DOI of article: https://doi.org/10.1063/5.0188257</p>
Data related to the article "A molecular perspective on induced charges on a metallic surface"
<p>Contains input files and data used to generate the figures of the article:</p> <p>A molecular perspective on induced charges on a metallic surface<br> (Giovanni Pireddu, Laura Scalfi, and Benjamin Rotenberg)</p> <p>arXiv: <a href="https://arxiv.org/abs/2110.11103">https://arxiv.org/abs/2110.11103</a></p> <p>The folder EXAMPLE_INPUT_FILES contains typical <a href="https://doi.org/10.21105/joss.02373">MetalWalls</a> (<a href="https://gitlab.com/ampere2/metalwalls">repository</a>) input files used to perform the simulations.</p> <p>The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper.</p> <p>The data files are named according to the ion distance considered:<br> - 'd1' corresponds to 1.50 Å;<br> - 'd2' corresponds to 3.14 Å;<br> - 'd3' corresponds to 5.40 Å;<br> - 'd4' corresponds to 7.03 Å;<br> - 'd5' corresponds to 15.00 Å.</p> <p>The data files are reported in three formats:<br> - induced charge density maps are in matrix format (arranged in several rows with each value corresponding to the values on the map).</p> <p> The coordinates of each point on the map are stored in the first row and first column.<br> - Solvent charge density maps are arranged in columns: (i) x coordinate, (ii) y coordinate, (iii) solvent charge density.<br> - Radial profiles are arranged in columns: (i) r, (ii) charge density, (iii) radial integral.</p>
data set to bioRxiv preprint 'Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation
<p>This is supporting data and software code for the following preprint in bioRxiv</p> <p><strong>Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation</strong></p> <p>https://www.biorxiv.org/content/10.1101/2022.04.18.488629v1</p>
Method Classification of Open Access INTACT Molecular Interaction data.
<p>Simple classification data derived from open access papers indexed in the INTACT database (https://www.ebi.ac.uk/intact/downloads) based on PSI-MI25 codes for interaction detection methods or participant detection methods based on the subfigure caption text. <br> <br> intact_records_and_captions_complete.tsv - This file links available text of subfigure captions to PSI-MI25 codes for the interaction detection method and participant detection method. </p> <p>evidx_run_file.txt - This file provides execution codes for the 'EvidX' machine learning text classifier (https://github.com/SciKnowEngine/evidX/releases/tag/v0.1.0)</p> <p> </p> <p> </p> <p> </p>
Dataset of molecular docking data of neuropeptides to acid-sensing ion channels
<p>The *.dock4 files are result files of molecular docking with the software Autodock Vina to the human ASIC1a closed state model, of the peptides FRRFa and KNFLRFa (FRRF.dock4, KNFLRF.dock4) that can be visualized with structure viewing programs such as UCSF Chimera on the closed ASIC1a model file (closed_ASIC_pH7.4.pdb). The file “FRRF_KNFLRF_complexes.pdb” provides the structures of selected poses of FRRFa and KNFLRFa peptides docked to the closed conformation of the human ASIC1a model.</p>
Supporting data for "Quantifying the Strength of a Salt Bridge by Neutron Scattering and Molecular Dynamics"
<p>Supporting data for the following published paper: Mason, Jungwirth, Duboué-Dijon, 2019, JPhysChemLett, 10, 3254-3259</p> <p>Contains both data from neutron scattering measurements and input simulation files necessary for reproduction of the work.</p>
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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.