Find research datasets worth reusing

Data set for manuscript "Optimal utilization of PMTCT of HIV services among adolescents under group versus focused antenatal care"

The derived variables in the data set are labeled "DER what variables they are derived from" except the variable "optimal utilization which is a composite outcome of other variables depending on HIV status as described in the manuscript. The variables "...cat" are categorized or recoded from an original numeric/ categorical variable The variables bin are used when a "cat" variable exists but further recoding is done to form a binary variable

Dataset for the manuscript: Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages.

Dataset for the manuscript: Modelling the within-host spread of SARS-CoV-2 infection, and the subsequent immune response, using a hybrid, multiscale, individual-based model. Part I: Macrophages. preprint, bioRxiv, 2022. DOI: 10.1101/2022.05.06.490883 Each zip file contains the raw computational data (as a gzip compressed tarball), YAML input files, as well as Python plotting scripts. The Python plotting scripts have dependencies on the packages: tarfile, multiprocessing, numpy, scipy, and matplotlib. Note that the Python plotting scripts plot directly from the gzip compressed tarballs. The corresponding code can be found on GitHub: https://github.com/Ruth-Bowness-Group/CAModel

Data files for the manuscript "Moth light traps perform better with vanes"

This upload contains the datasheets for the manuscript titled "Moth light traps perform better with vanes: A comparison of different designs" submitted to the Journal of Applied Entomology in May 2022. Datasheets contain the raw data, species list and a complete list of R packages used.

opencc-by-nc-4.0May 2022View details →

Raw data files for "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" manuscript

Raw data files for a manuscript "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" published in Chemical Science. <a href="https://doi.org/10.1039/D2SC01041K">https://doi.org/10.1039/D2SC01041K</a> The files are organized by manuscript figure names and are in a simple text or CSV format. The headers contain the necessary information such as column designations, units, etc.

Project files provided as supporting information to the manuscript "Information-theoretical measures identify accurate low-resolution representations of protein configurational space"

The dataset contains the following compressed folder: -Notebooks.zip: This folder contains:   -python_script:         -RESREL.py: script performing the clusterization and computing the relevance resolution curves         -random_curves.py: script generating the random value and computing the corresponding RES-REV curves_s         -Cluster_distance_matrix.py: script returning the distance among clusters for a given partition.   -python_notebook:         -Exploratory_analysis.ipynb:  Analysis performed on the 12-protein_dataset         -DMAPS_ANTI.ipynb: Diffusion Map for the Antibody         -DMAPS_COV_1ake.ipynb: Diffusion Map + Inter-Intra state decomposition of covariance for 1ake Packages required for the usage of these python scripts/notebooks:   -numpy   -pandas   -matplotlib   -seaborn   -multiprocessing   -scipy   ======== RAW DATA ======== The raw data produced and employed in this study are available on a Google Drive folder at the following address: https://drive.google.com/drive/folders/1PasAUCgpR5-gdzUVEdyusgZIayQN0Le9 In this folder, together with the compressed Notebooks.zip folder, one can fin the compressed folder Data.zip, within which the following data are present: -12-protein_dataset:     -md.mdp: the .mdp file used in the MD simulations     -PROTEIN_PDB_CODE:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves, sel=[all, CA, CB]         -RMSD_{sel}.npy: the RMSD matrix, sel=[all, CA, CB]         -npt.gro:protein+water+ions structure @TEO the equilibration (NVT+NPT)         -MSR_df.csv: a dataset containing the following columns                   'area' : area behind the Relevance-Resolution curve;                   'selection': the atomic selection (['all', 'CA', 'CB']) used to compute the RMSD matrix used for the clusterization (and consequently the Relevance-Resolution curves)                   'method': the linkage measure used in the clustering procedure, an integer in [0,6];                   'method_name': the linkage measure used in the clustering procedure, a string in ['average','ward','complete','single','centroid','median','weighted'];                   'rmsd_mean': the mean value of the rmsd vector along the trajectory computed wrt the first frame;                   'rmsd_var': the variance of the rmsd vector along the trajectory computed wrt the first frame;                   'rgy_mean': the mean value of the radius of gyration  along the trajectory;                   'rgy_var': the variance of the radius of gyration  along the trajectory;                   'rmsf_mean': the mean value of the rmsf;                   'rmsf_var': the variance of the rmsf;                   'RMSD_M_mean': the mean value of the RMSD matrix.                   'RMSD_M_var': the variance of the RMSD matrix.   -Random:     -curves.npy= 100K Relevance-Resolution Random curves for M=40001     -curves_s.npy= 100K Relevance-Resolution Random curves for M=15000   -validation_dataset:     -antibody:         -Hk_CB.npy & Hs_CB.npy: the Rel & Res curves         -RMSD_CB.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters     -1ake:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves         -RMSD_{sel}.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters         -intra_{m}.npy: the intra-cluster covariance matrix         -inter_cov_{m}.npy: the inter-cluster correlation matrix   NOTE ===== The matrices of the cluster distances for adenylate kinase and antibody have been computed through the script Cluster_distance_matrix.py. These matrices have not been included in the dataset because of their large size; the raw data are however available upon request.

Other supporting data for our manuscript "Mapping the Single Cell Transcriptomic Response of Murine Diabetic Kidney Disease to Therapies"

Other supplementary data for our paper "Mapping the Single Cell Transcriptomic Response of Murine Diabetic Kidney Disease to Therapies"

opencc-by-4.0Apr 2022View details →

Raw data of manuscript "Tapered fibertrodes for opto-electrical neural interfacing in small brain volumes with reduced artefacts"

This dataset contains the raw data for the paper titled "Tapered fibertrodes for opto-electrical neural interfacing in small brain volumes with reduced artefacts".

Supplementary material for manuscript Building Archean cratonic roots

Scripts and raw data used to plot Figures 1 and 6 of the manuscript "Building Archean cratonic roots" submitted to the Research Topic: "Interior Dynamics and Chemistry of Earth and Other Rocky Planets: Past and Present" at the journal "Frontiers in Earth Science: Solid Earth"

Dataset for the Manuscript: Structural and mechanistic insights into the cleavage of clustered O-glycan patches-containing glycoproteins by mucinases of the human gut (in revision)

This dataset provides the classical and QM/MM MD simulation trajectory data to the manuscript: Structural and mechanistic insights into the cleavage of clustered O-glycan patches-containing glycoproteins by mucinases of the human gut The data set contains classical MD simulations of AM0627 with three substrate peptides P1, P2, P9, and BT4244 with glycopeptides, as well as QM/MM metadynamics simulations for our manuscript. PDB files for Figures 4,5 and Figure S5-8,10 are also included.

Supplementary material for the manuscript "Simple synthesis of massively parallel RNA microarrays via enzymatic conversion from DNA microarrays"

This dataset contains: <ul> <li> a .txt file with the design of the Agilent SurePrint DNA microarray AMADID 086693, containing all sequences and their position on the surface </li> <li> the following raw microarray scans:</li> </ul> <ol> <li>Image of T7RNAP crystal structure, scanned at 635 nm (Cy5) (polymerase) ("01_T7RNAP image_Cy5")</li> <li>Image of T7RNAP crystal structure, scanned at 532 nm (Cy3) (dsDNA template strand) ("02_T7RNAP image_Cy3")</li> <li>Image of T7RNAP crystal structure, scanned at 488 nm (FAM) (RNA product strand) ("03_ T7RNAP image_FAM")</li> <li>Scan of the Agilent SurePrint DNA microarray (AMADID 086693) after hybridization with a Cy3-labeled oligonucleotide to untreated DNA (Block 1) and RNA as the product of the conversion process (Block 2) ("04_AgilentArray - Block 1 (untreated) vs Block 2 (converted)")</li> </ol>

Dataset for the Manuscript: Demonstration of optically-driven plasmonic nanomotors designed by deep learning networks

This repository contains the data corresponding to the manuscript "Demonstration of the optically-driven plasmonic nanomotor designed by deep learning networks." It consists of 5 parts: Machine learning, Numerical analysis, Rotation measurement, Scattering measurement, and Supplementary information. The code for the machine learning algorithm is available at "https://github.com/mintaechung/Nanomotor_Predictor_Generator."   <ul> <li>'Machine_learning.zip': Correlation between optical torques calculated by SIE and predicted by trained CNN, Objective loss functions at the 1st iteration, and the torque distribution of the initial randomset and the output of the nanorotor generator after the 3rd iteration.</li> <li>'Numerical_analysis.zip': MATLAB codes to retrieve 'Moments', 'Field intensity distribution', 'Poynting vectors', and 'Torques'. </li> <li>'Rotation_measurement.zip': Raw videos, Intensity profiles of ROI, Rotation measurement results.</li> <li>'Scattering_measurement.zip': Scattering intensity measurement with reference light.</li> <li>'Supplementary_Info.zip': Random geometry generation, Optical torques of 6 blades, Expanded structure, Shrinkage, Polarization independence, Angular momentum, and Machine learning progress.</li> </ul>

Datasets and code of the manuscript 'Insights into the Aerodynamic versus Radiometric Surface Temperature Debate in Thermal-based Evaporation Modeling'

This contains the datasets and codes that were used to generate the results and discussions in the manuscript

Data for WRR submitted manuscript 2021WR031703R

Dataset from global survey on Data-as-a-Service adoption by water and wastewater utilities.

Imaging data (part 1) for the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice"

This archive contains part 1 of the raw imaging data of the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice".

Imaging data (part 2) for the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice"

This archive contains part 2 of the raw imaging data of the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice".

Supplementary data and code of the manuscript: "Strong evidence for the adaptive walk model of gene evolution in Drosophila and Arabidopsis"

This repository contains all data tables ad code to reproduce the analysis performed in "Strong evidence for the adaptive walk model of gene evolution in Drosophila and Arabidopsis".

Raw data for the manuscript entitled "Forest age and topographic position jointly shape the species richness and composition of vascular plants in karstic habitats"

Doline surveys from the Mecsek Mountains, Hungary. Transects were established with north to south orientation across each doline, traversing their deepest point. Transects began and ended on doline rims, and consisted of 1 m  × 1 m plots spaced at 2 m intervals (94, 89, 90 and 99 plots in the different forest age classes, respectively; 372 plots in total). We recorded the presence/absence data of shrubs and herbs in each plot. Fieldwork was carried out between 2007 and 2019 from June to August, at the peak of the growing season.

Raw datasets and media accompanying the manuscript: Extracellular Vesicles (EVs) Are Copurified with Feline Calicivirus, yet EV-Enriched Fractions Remain Infectious

Raw datasets and media accompanying the manuscript: Extracellular Vesicles (EVs) Are Copurified with Feline Calicivirus, yet EV-Enriched Fractions Remain Infectious

Data set related to the manuscript "Understanding the chemical shifts of aqueous electrolyte species adsorbed in carbon nanopores"

Graphical files in the agr format for all the figures in the manuscript entitled "Understanding the chemical shifts of aqueous electrolyte species adsorbed in carbon nanopores". Examples of input files for the density functional theory, lattice and molecular dynamics simulations are also provided.

Data for manuscript sumitted to Open Research Europe, entitled "Low-resistivity, high-resolution W-C electrical contacts fabricated by direct-write focused electron beam induced deposition"

These are the data obtained experimentally and used to draw the figures in the article submitted to Open Research Europe