Find research datasets worth reusing

Supplementary data for "Influence of prey availability on habitat selection during the non-breeding period in a resident bird of prey"

Abstract Background: For resident birds of prey in the temperate zone, the cold non-breeding period can have strong impacts on survival and reproduction with implications for population dynamics. Therefore, the non-breeding period should receive the same attention as other parts of the annual life cycle. Birds of prey in intensively managed agricultural areas are repeatedly confronted with unpredictable, rapid changes in their habitat due to agricultural practices such as mowing, harvesting, and ploughing. Such a dynamic landscape likely affects prey distribution and availability and may even result in changes in habitat selection of the predator throughout the annual cycle. Methods:  In the present study, we 1) quantified barn owl prey availability in different habitats across the annual cycle, 2) quantified the size and location of barn owl breeding and non-breeding home ranges using GPS-data, 3) assessed habitat selection in relation to prey availability during the non-breeding period, and 4) discussed differences in habitat selection during the non-breeding period to habitat selection during the breeding period. Results: The patchier prey distribution during the non-breeding period compared to the breeding period led to habitat selection towards grassland during the non-breeding period. The size of barn owl home ranges during breeding and non-breeding  were similar, but there was a small shift in home range location which was more pronounced in females than males. The changes in prey availability led to a mainly grassland-oriented habitat selection during the non-breeding period. Further, our results showed the importance of biodiversity promotion areas and undisturbed field margins within the intensively managed agricultural landscape.  Conclusions: We showed that different prey availability in habitat categories can lead to changes in habitat preference between the breeding and the non-breeding period. Given these results we show how important it is to maintain and enhance structural diversity in intensive agricultural landscapes, to effectively protect birds of prey specialised on small mammals. Hereafter we provide the datasets and R script to reproduce the resource selection functions.

openapache2.0Dec 2022View details →

fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions - supplementary data.

fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions - supplementary data.Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.

Supplementary Data for "Substrate-Assisted Mechanism for the Degradation of N-glycans by a Gut Bacterial Mannoside Phosphorylase"

This dataset contains atomic coordinates of the molecular dynamics simulations described in "Substrate-Assisted Mechanism for the Degradation of N-glycans by a Gut Bacterial Mannoside Phosphorylase" by M. Alfonso-Prieto, I. Cuxart, G. Potocki-Véronèse, I. André and C. Rovira, published in ACS Catalysis (https://doi.org/10.1021/acscatal.3c00451). Further details on the setup of the simulations can be found in the Supplementary Information of the article.  If you use this dataset, please cite this zenodo upload (https://doi.org/10.5281/zenodo.7704778), as well as the the original journal article (https://doi.org/10.1021/acscatal.3c00451).  This dataset is organized in the following folders: Snapshots_Figures_Main_Text.zip, that contains a README.txt file and: - Figure_3 contains representative structures (atomic coordinates) of the hexameric form of UhgbMP in complex with 3 different disaccharide molecules, Man-b-(1,4)-GlcNAc, Man-b-(1,4)-Glc and Man-b-(1,4)-Man. - Figure_4 contains representative structures (atomic coordinates) of the hexameric form of UhgbMP at the three minima observed along the reaction coordinate corresponding to phosphorolysis of the disaccharide Man-b-(1,4)-GlcNAc: Michaelis complex (MC), transition state (TS) and product (P) complex. Files in this dataset are in PDB format. For all structures, the solvation box (water and ions) has been stripped to reduce file size. See README.txt inside <a href="https://zenodo.org/api/files/f3836540-b7b6-4820-87b3-7fa5dff7840c/Snapshots_Figures_Main_Text.zip">Snapshots_Figures_Main_Text.zip </a>for more information.

Supplementary Data: Global fits if simplified models for dark matter with GAMBIT II. Vector dark matter with an s-channel vector mediator

This record contains the YAML files, data files, and some of the plotting scripts for: "Global fits of simplified models for dark matter with GAMBIT II. Vector dark matter with an s-channel vector mediator". Samples have been created using GAMBIT and figures can be reproduced with pippi. Plotting scripts (*.pip) are designed to work with either the original version of pippi 2.1 or the forked unreleased version. The provided scripts do not reproduce all the figures in the paper exactly. To save storage space, all samples have been compressed using <code>tar</code>. To inflate each dataset after downloading run <code>tar -zxvf <samples>.hdf5.gz</code>. To facilitate uploading to Zenodo, several of the data files have been thinned to only include enough points to reproduce plots.

Supplementary Data: Collider constraints on electroweakinos in the presence of a light gravitino

This record contains the full dataset generated for the study "Collider constraints on electroweakinos in the presence of a light gravitino" by the GAMBIT Collaboration. The record also includes a GAMBIT configuration file and example scripts for plotting. See the README.md file for further details.

Supplementary data for the paper "Visual integration of omics data to improve 3D models of fungal chromosomes"

<ul> <li>13 parameter files (*.YML) used by the 3DGB workflow to produce models of 3D genomes.</li> <li>13 3D genomes structures (*.PDB).</li> <li>4 animated GIF of representative structures.</li> <li>1 XLSX file that lists raw (Hi-C and ChIP-seq) data used in this study and the associated analysis.</li> </ul>

opencc-by-4.0Feb 2023View details →

Spray impact onto a hot solid substrate: film boiling suppression by lubricant addition. Supplementary Data

This is a Supplementary Data for a paper entitled "Spray impact onto a hot solid substrate: film boiling suppression by lubricant addition" by Gajevic Joksimovic et al. Frontiers in Physics (2023). Data used for plotting of figures Datasets for Fig. 5:  Number at the end of the file name corresponds to the volumetric lubricant concentration used. <ul> <li>      Dataset_Figure5 TimeTemperatatureFlux  Concentration 0.97.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 1.09.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 1.26.txt </li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 1.49.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 1.82.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 2.34.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 3.28.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux Concentration 5.47.txt</li> <li>      Dataset_Figure5 TimeTemperatatureFlux PureWater.txt</li> </ul> Datasets for Fig. 11: <ul> <li>Dataset_Figure11 PHI Omega Omega nu.txt</li> </ul> Supplementary videos The supplementary videos for Fig. 8: <ul> <li>supplementary video Figure8a.mp4</li> <li>supplementary video Figure9b.mp4</li> <li>supplementary video Figure9c.mp4</li> </ul> The supplementary video for Fig. 13 <ul> <li>supplementary video Figure13.mp4</li> </ul>

opencc-by-nc-4.0Mar 2020View details →

Supplementary phylogenetic data for Rouïl et. al. 2020 "The protector within: Comparative genomics of APSE phages across aphids reveals rampant recombination and diverse toxin arsenals"

Supplementary phylogenetic data for Rouïl et. al. 2020 "The protector within: Comparative genomics of APSE phages across aphids reveals rampant recombination and diverse toxin arsenals"   The data set consists of the following sub-directories: 1) "APSE_conserved_proteins_alns": Single-copy conserved genes codon sequences and alignments in FASTA format. 2) "APSE_phylogeny": Files used for APSE phylogenetic and recombination analyses. 3) "APSE_reannotations": GenBank-formatted files of the assemblies and re-annotations of APSE phages. Newly-sequenced phages deposited at the European nucleotide Archive are also included. ***New in this version*** 4) "APSE_toxin_lyzozyme": Files used for APSE toxin-cassette and lyzozyme-related gene phylogenies. 5) "Arsenophonus_PHASTER": PHASTER phage annotation output files organised by organisim and contig/scaffold. 6) "Hamiltonella_drafts": Newly-sequenced low-coverage draft Hamiltonella genomes in FASTA format. 7) "Hamiltonella_phylogeny": files used for Hamiltonella phylogenetic analysis.   See enclosed README.txt file for more details.   * ver. 1.1.1: Updated annotations for APSE genomes including inteins missing in previous annotation files.

opencc-by-4.0May 2023View details →

Supplementary Data: Fast and accurate AMS-02 antiproton likelihoods for global dark matter fits

The files in this record contain supplementary data for the study, "Fast and accurate AMS-02 antiproton likelihoods for global dark matter fits".  Samples have been created using <a href="https://gambitbsm.org/" target="_blank" rel="noopener">GAMBIT</a> and figures can be reproduced with <a href="http://github.com/patscott/pippi" target="_blank" rel="noopener">pippi</a>.

Supplementary datasets: sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data (Ng et al.)

This repository contains data files from the manuscript Ng et al. "sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data". Directories Please untar the sciCSR-data-files.tar.gz archive. Folder "Simulated_data" <ul> <li>'simulated_IGHC_reads' folder: containing list of simulated data (FASTQ sequence files and aligned BAM files) to test the accuracy of commonly used RNA-seq aligners (STAR, HISAT2) to distinguish sterile and productive heavy-chain transcripts. The code to generate these data is in the repository https://github.com/Fraternalilab/sciCSR-analysis.</li> <li>'simulated_transitions.RData': .RData file containing list of Seurat objects of simulated datasets of different number of cells, to test the robustness of sciCSR-inferred transitions across different dataset sizes.</li> </ul> Folder "Seurat_objects" <ul> <li>'human_Bcells_atlas_IGHC_NMF_rank.rds': Nonnegative matrix factorization (NMF) results to derive isotype signatures from the human B cell atlas (see below).</li> <li>'mouse_Bcells_atlas_IGHC_NMF_rank.rds': NMF results to derive isotype signatures from the mouse B cell atlas (see below)</li> <li>'Human_Bcells_atlas_IGHC.rds': Seurat object containing cells forming the 'human B cell atlas' (i.e. merging data from Stewart et al (https://doi.org/10.3389/fimmu.2021.602539) and King et al (https://doi.org/10.1101/2020.04.28.054775))</li> <li>'mouse_Bcells_atlas_IGHC.rds': Seurat object containing cells forming the 'mouse B cell atlas' (i.e. merging data from Mathew et al (https://doi.org/10.1016/j.celrep.2021.109286) and Luo et al (https://doi.org/10.1186/s13578-022-00795-6))</li> <li>'Stewart_HumanPeripheral_Bcells_IGHC.rds': Seurat object containing cells from the Stewart et al (https://doi.org/10.3389/fimmu.2021.602539) peripheral blood B cell atlas.</li> <li>* 'King_HumanTonsil_Bcells_IGHC.rds': Seurat object containing cells from the King et al. (https://doi.org/10.1101/2020.04.28.054775) human tonsilar B cell atlas.</li> <li>'Kim_Covid_Bcells_IGHC.rds': Seurat object containing cells from the Kim et al. (https://doi.org/10.1038/s41586-022-04527-1) time-course scRNA-seq data on human B cell response to SARS-CoV-2 vaccine.</li> <li>'Gomez_AID_VDJ_IGHC.rds': Seurat object containing cells from the Gómez-Escolar et al. (https://doi.org/10.15252/embr.202255000) Aicda mouse knockout scRNA-seq data.</li> <li>'Hong_IL23_Bcells_IGHC.rds': Seurat object containing cells from the Hong et al. (https://doi.org/10.4049/jimmunol.2000280) Il23 p19 mouse knockout scRNA-seq data.</li> <li>'scIFNg.rds': Seurat object containing scRNA-seq data of time-course in vitro culture of B cells stimulated with interferon gamma generated in this work.</li> </ul>

opencc-by-4.0Jan 2023View details →

Supplementary data for the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand"

Binarized cutouts (black=pore, white=soil) of 3D CT images of soil samples from loam and sand together with geometrical descriptors and diffusive properties computed on these cutouts. The geometrical descriptors include, among others, porosity, specific surface area, geodesic tortuosity, geometric tortuosity, constrictivity, mean chord length and mean of spherical contact distribution. Diffusion is quantified by the so-called M-factor which equals the ratio of the effective and intrinsic diffusivity. This data supplements the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand". Additional information can be found there.

NewSOC, supplementary information to WT2.5.4 "Cells with honeycomb structured oxygen electrodes": electrochemical and post-mortem data sets.

These are data set, related to participation of the IEN in project NewSOC. It includes results of the SEM-EDS analysis of the cells with hexagonal current collecting net and electrochemical performance data, both EIS and C-V characteristics. Results are grouped in zip archives, named according to cell design, “infill-net”. Compositions: LNF – LaNi0.6Fe0.4O3 (net) LSC – La0.6Sr0.4CoO3-d (infill) LSF – La0.5Sr0.5FeO3-d (infill) LSCCF – La0.6Sr0.4Co0.15Cu0.05Fe0.8O3-d (net) PCM – Pr0.5Ca0.5MnO3 (net) BSCFM – Ba0.5Sr0.5Co0.725Fe0.2Mo0.075O3-d (infill)   Data presentation. C-V characteristics: This is text files, generated by Zahner galvanostat, with self-decriptional titles. “05iv_650c_100h2+100h2o_500air.txt” –  measurement at 650°C, 100 mL/min H2 and 100 mL/min H2O on fuel side, 500 mL/min of air on air side. EIS data: EIS results were extracted from proprietary binary files, generated by Zahner galvanostat, and raw data is generally meaningless except the owners of such hardware. So, extracted EIS can be found in Excel files, used in analysis, in sheet “Experimental”. Other sheets in xlsx include some metadata (“info”), results of the equivalent circuit fit (“fit”) and some plots. Fit results might not be relevant.   SEM Post-mortem results presented as SEM images (tif or jpg files) and pdf files with results of the EDS analysis. LSC-LNF (air flow 1 L/min, current density 0.25 A/cm2) test_1_07:   03_eis20200917142808.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H2; 05_eis20200917123105.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 08_eis20200917123857.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 10_eis20200917131537.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; test_1_08: 03_eis20200917125707.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H2; 09_eis20200917130019.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.09 H2+ 0.21 H2O; 10_eis20200917130600.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.06 H2+ 0.14 H2O; 12_eis20200917130737.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.12 H2+ 0.28 H2O; test_3_14: 01_eis20210517102042.xlsx– EIS, SOFC, 700°C, Flows L/min: F:0.1 H2+0.1 N2; 05_eis20210517102625.xlsx– EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 07_eis20210517102305.xlsx– EIS, SOEC, 700°C, flows L/min: F:0.06 H2+ 0.14 H2O; SEM (post-mortem after test_1_07) ogniwo_310_2020  ****.jpg - surface   BSCMF-PCM (SOFC, air flow 0.5 L/min) test_2_14 01eis_700c_cc4a_100h2+100n2_500air_eqc20220110112836.xlsx –700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02eis_700c_cc4a_100h2+100h2o_500ai_eqc20220110112724.xlsx –700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04eis_650c_cc3a_100h2+100h2o_500ai_eqc20220110112503.xlsx–650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06eis_650c_cc3a_100h2+100n2_500air_eqc20220110112332.xlsx –650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 07eis_625c_cc3a_100h2+100n2_500air_eqc20220110112214.xlsx –625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 08eis_625c_cc3a_100h2+100h2o_500ai_eqc20220110111834.xlsx–625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; test_1_67 01_eqc20220831134628.xlsx–700°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02_eqc20220831134724.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04_eqc20220831135442.xlsx–650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 06_eqc20220831135622.xlsx - 650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08_eqc20220831135801.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 09_eqc20220831135933.xlsx –650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; SEM (post-mortem of the test_2_14) 493-2021-1.pdf, 493-2021-1i.pdf, 493-2021-2.pdf, 493-2021-2-2.pdf, 493-2021-2-3.pdf –cross-sections with EDS 493_2021_*_**.tif  - cross-sections   BSCMF-LSCCF (SOFC, air flow 0.5 L/min)                                test_2_08 01_eis20211104144342.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 03eis_700c__eis20211108102241.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04eis_700c__eis20211108102401.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08eis__eis20211110094642.xlsx - 650°C, 0.1875  A/cm2 Flows L/min: F:0.1 H2+0.1 N2 10eis__eis20211110094945.xlsx - 650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 11eis__eis20211110101358.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 13eis__eis20211110100837.xlsx- 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2;                                test_2_26 04_eqc20220817114103.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06_eqc20220817121529.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 07_eqc20220802084119.xlsx - 650°C, 0.1875  A/cm2 Flows L/min: F:0.1 H2+0.1 08_eqc20220802084616.xlsx - 650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 10_eqc20220802150705.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 11_eqc20220802150108.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; SEM (post-mortem of the test_2_26) 661_BSCMF_LSCCF_p.pdf  – cross-section with EDS 661_BSCMF_LSCCF_PM.pdf - surface with EDS 661_BSCMF_LSCCF_p_01.tif, 661_BSCMF_LSCCF_p_02.tif, 661_BSCMF_LSCCF_p_03.tif, 661_BSCMF_LSCCF_p_04.tif  -  cross-section, infill zone 661_BSCMF_LSCCF_p_05.tif, 661_BSCMF_LSCCF_p_06.tif - cross-section, net zone zone 661_BSCMF_LSCCF_PM_**.tif  - surface   LSF-LSCCF (SOFC, air flow 0.5 L/min) test_1_65 01_eqc20220816105347.xlsx - 700°C, 0. 1875 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 02_eqc20220816105941.xlsx - 700°C, 0. 1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04_eqc20220816112311.xlsx - 650°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06_eqc20220816111640.xlsx - 650°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 07_eqc20220816142436.xlsx- 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 08_eqc20220816142842.xlsx-625°C, 0.625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; SEM (post-mortem) 663_LSF_LSCCF_p.pdf – cross-section with EDS 663_LSF_LSCCF_PM.pdf - surface with EDS 663_LSF_LSCCF_P_GR_**.tif – cross-section of the cell 663_LSF_LSCCF_P_LSCCF_**.tif – surface of the LSCCF grid 663_LSF_LSCCF_PM_**.tif - surface of the LSF infill     LSF-PCM (SOFC, air flow 0.5 L/min) tests_1_66 01_eqc20220831133210.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02_eqc20220831133409.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 03_eqc20220831133928.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 05_eqc20220831134048.xlsx - 650°C, 0.0625  A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 06_eqc20220831134142.xlsx - 650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08_eqc20220831134237.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 10_eqc20220831134412.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; SEM (post-mortem) 658_LSF_PCM_p.pdf – cross-section with EDS 658_LSF_PCM_PM.pdf - surface with EDS 658_LSF_PCM_P_LSF_**.tif  – cross-section, infill zone 658_LSF_PCM_P_pcm_**.tif - cross-section, net zone 658_LSF_PCM_PM_**.tif - surface description.pdf - pdf version of this information.

opencc-by-4.0Jul 2022View details →

Supplementary Movies and Source Data for: Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation

Supplementary Movies and raw data for the manuscript: "Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation": Source_Data.zip: Supplementary Code, Supplementary Data and Weka Analysis Lan_supplementary_movies_AVI.zip: Supplementary movies as AVI Lan_supplementary_movies_MP4.zip: Supplementary movies as MP4 Lan_raw_movies.zip: Raw TIFF stacks of the movies. Lan_supplementary_movies.zip: Old version of the movies.

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data)

This dataset contains supplementary replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". In particular, it contains a new version of our `final_raw_dips.tar.gz` protein pair representations which now contain (1) residue-level annotations for intrinsic disorder regions (IDRs) as well as (2) a copy of each protein pair representation in the HDF5 file format for programming language-agnostic read capabilities. In addition, this record also contains (3) raw MSAs (in HDF5 file format) generated for each protein pair using Jackhmmer and AlphaFold's small version of the Big Fantastic Database (BFD). Lastly, this record contains (4) PDB metadata derived for each DIPS-Plus complex using Graphein's PDBManager API as well as (5) structure-based (i.e., FoldSeek-based) training and validation splits of the dataset's complexes in the form of respective text files containing the file paths of complexes assigned to each split.

opencc-by-4.0Jul 2023View details →

Supplementary Data for Low-loss stable storage of 1.2 Angstrom X-ray pulses in a 14 m Bragg cavity

Supplementary Data for Margraf, R. et al. "Low-loss stable storage of 1.2 Angstrom X-ray pulses in a 14 m Bragg cavity," Nature Photonics, 2023.

opencc-by-4.0Jul 2023View details →

Self-supervised learning of seismological data reveals undocumented eruptive sequences at the Mayotte submarine volcano - Supplementary Materials

The following files are shared:                 - The scripts used to train the model and generate the figures of the article                 - The input images used to train the model as well as the final outputs (embedding matrix and the associated filenames matrix)                 - The clusters organization with their associated images

Publication & Supplementary data: Pro-health compounds and antioxidant activity of 65 potato cultivars

Metadata (climatic conditions, list of varieties, field plan, etc.) and data (carotenoid content, vitamin C content, radical scavenging activity DPPH and FRAP, yellow index) related to the paper of Tatarowska et al., "The content of total carotenoids, vitamin C and antioxidant properties of 65 potato cultivars characterised under the European project ECOBREED" published in Int. J. Mol. Sci. 24 (2023), 11716.

opencc-by-4.0May 2023View details →

Supplementary data and summary statistics - Genetic influences on circulating retinol and its relationship to human health

Summary statistics from the circulating retinol GWAS See - GWAS_summary_stats_README.txt for details of these files and the header names. METSIM+INTERVAL meta-analyses have a sample size of 17268. The full meta-analysis that includes ATBC+PLCO has a sample size of 22274. Please cite the following if you use any of these data - Reay, W.R. et al. Genetic influences on circulating retinol and its relationship to human health. Nature Communications (2024). By downloading these summary statistics, investigators agree to the following: <ol> <li>Investigators acknowledge that these data are provided on an “as-is” basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose.</li> <li>Investigators will not cross-post these data or make them available elsewhere – this website is the definitive source for these data without express written permission from the study corresponding authors.</li> <li>Investigators will never attempt to identify any participant who contributed to these data.</li> <li>Any commercial or for-profit use of these data is forbidden unless express permission is sought from the study corresponding authors.</li> <li>Investigators will cite the associated manuscript when using these data.</li> </ol> Supplementary data from the circulating retinol GWAS phenome-wide Mendelian randomisation study 1. MR_retinol_as_exp - full output from the MR-pheWAS using circulating retinol as the exposure

opencc-by-4.0Apr 2023View details →

Data and Supplementary Material for "Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations" by Jensen et al.

Data and Supplementary Material for the manuscript “Insights into Lightning K-Leader Initiation and Development from Three Dimensional Broadband Interferometric Observations” by Jensen et al., submitted to Journal of Geophysical Research: Atmospheres. Further description in included PDF (01file_description.pdf)