Find research datasets worth reusing

opencc-by-4.0Jul 2023View details →

Supplementary data for multidimensional drivers of mercury distribution in global surface soils

Global distribution of Hg in surface soils predicted by a machine learning method.  Random forest modeling. Latitude 1 degree by longitude 1 degree.

opencc-by-4.0Jul 2023View details →

Supplementary Datasets for: 'A processing and analytics system for microscopy data workflows: the Pycroscopy ecosystem of packages'

The repository contains four independent datasets that are a part of the publication (<a href="https://arxiv.org/abs/2302.14629">arXiv:2302.14629</a>), which delineates the capabilities of the Pycroscopy ecosystem of packages. The details of the individual datasets can be found below.  1) bfo_iv_final.hf5: Dataset of I-V curves captured by conductive atomic force microscopy on a BiFeO3 sample. The data has been transformed so that we plot not the log of the current density (J) as a function of the square root of the electric field. The dataset was originally presented in the paper 10.1038/s41467-017-01334-5  2) bto_atomic.dm3: Atomically resolved data BaTiO3 thin film acquired with scanning transmission electron microscopy. These were originally captured in the dm3 file format. This dataset was a part of the publication: doi.org/10.1002/adma.202106426 3) EELS_STO.dm3: Scanning transmission electron microscope (STEM)-Electron energy loss spectroscopy (EELS) dataset of SrTiO3. 4) STO-stack.h5: High-angle annular dark-field imaging (HAADF) scanning transmission electron microscope (STEM) image stack of SrTiO3. This image stack contains 25 images.

opencc-by-4.0Oct 2022View details →

Data and supplementary material for the paper "Development of an IntelliCage based Cognitive Bias Test for Mice."

All raw data, R scripts for analysis and the supplementary material related to the paper "Development of an IntelliCage based Cognitive Bias Test for Mice." are available to the scientific public here. A preprint version of the paper will be published on bioRxiv.  Version 2 contains R scripts, version 1 does not. Version 3: For better clarity, the data were saved as .ods files. Each .ods file contains the data for one developmental step. The R scripts are still available as .txt files. In addition, an ARRIVE checklist was added. Version 4: xlsx instead of ods fiels Version 5: Extended supplemet PDF file Added GroupTwo_Entries and GroupThree_Entries txt files A pre-print version can be found at bioRxiv: https://www.biorxiv.org/content/10.1101/2022.10.19.512853v1

Supplementary data of article Integrating Data-Driven and Hydraulic Modelling with Acoustic Sensor Information for Improved Leak Location in Water Distribution Networks

This dataset was generated within the research thesis of Axel Hutomo, under the supervision of Leonardo Alfonso and Ioana Popescu at IHE Delft, and it is published as supplementary data for the article Integrating Data-Driven and Hydraulic Modelling with Acoustic Sensor Information for Improved Leak Location in Water Distribution Networks, currently under review.  The Excel sheet provides information about the datasets produced to integrate acoustic sensor data and hydraulic model output data, to be used by the Machine Learning model. The acoustic sensor data were obtained by extracting several features in time and frequency domains from each audio file coming from acoustic sensors, whereas hydraulic model data was obtained by modelling these leaks using a pressure-independent analysis. The Python code shows the building of the ANN for leakage modelling prediction, integrating the two datasets above, for different leak rates.

Supplementary Data and Codes for "Exclusive seismoacoustic detection and characterisation of an unseen and unheard fireball in the North Atlantic" by Stephen P. Hicks and Sandro B. Matos, et al.

Supplementary Dataset containing windowed seismic traces for the 29 June 2022 fireball event near the Azores in the North Atlantic, as studied in the manuscript entitled, "Exclusive seismoacoustic detection and characterisation of an unseen and unheard fireball in the North Atlantic" by Stephen P. Hicks and Sandro B. Matos, et al. A Python Jupyter Notebook is also provided that reproduces the main figures of the paper.

Supplementary Files and Data of 'Live-bearing cockroach genome reveals convergent evolutionary mechanisms linked to viviparity in insects and beyond'

Live birth (viviparity) has arisen repeatedly and independently among animals. We sequenced the genome and transcriptome of the viviparous Pacific beetle-mimic cockroach and performed comparative analyses with two other viviparous insect lineages, tsetse flies and aphids, to unravel the basis underlying the transition to viviparity in insects. We identified pathways undergoing adaptive evolution for insects, involved in uro-genital remodeling, tracheal system, heart development, and nutrient metabolism. Transcriptomic analysis in the cockroach and tsetse viviparity reveals that uterine remodeling and nutrient production are increased and the immune response is altered during pregnancy, facilitating structural and physiological changes to accommodate and nourish the progeny. These patterns of convergent evolution of viviparity among insects, together with similar adaptive mechanisms identified among vertebrates, highlight that the transition to viviparity requires changes in uro-genital remodeling, enhanced tracheal and heart development (corresponding to angiogenesis in vertebrates), nutrient metabolism, and shifted immunity in all animal systems.

opencc-by-4.0Apr 2023View details →

Supplementary Data: Identification of experimentally-supported poly(A) sites in single-cell RNA-seq data with SCINPAS

Supplementary data for the SCINPAS analysis as part of the manuscript "Identification of experimentally-supported poly(A) sites in single-cell RNA-seq data with SCINPAS". It includes the output of SCINPAS, available here: <a href="https://github.com/zavolanlab/SCINPAS">https://github.com/zavolanlab/SCINPAS</a>, used for the analyses. Additionally, the scripts and data for the comparison with other tools is provided. Please read the README.md for more information.

Supplementary Data and Code: Change Point Analysis to decode Economic Crisis Information

Raw data, results and Python code of the corresponding publication "Efficient Multi-Change Point Analysis to decode Economic Crisis Information from the S&P500 Mean Market Correlation" (accepted in: Entropy; Section: Complexity; Special Issue: Complexity in Finance). The change point analysis can be performed using the <a href="https://anticpy.readthedocs.io/en/latest/">documented</a> Python package <a href="https://github.com/MartinHessler/antiCPy">antiCPy</a>. Some further helpful Python scripts are provided here under a GNU General Public License v3.0. In Data_Generation you can find a list of <ol> <li>S&P500 companies which are considered in the analysis,</li> <li>a jupyter notebook to create the correlation time series.</li> </ol> Data_Preprocessing contains the <ol> <li>S&P500 mean market correlation Financial_Time_Series_Centered_Interval__42days.csv,</li> <li>the Python code to thin it,</li> <li>the thinned data saved as .npy file,</li> <li>the time scale is saved <ul> <li>as integer numbers in thinned_time_thinning40.npy,</li> <li>as datetime in TimeScale_FinancialData.npy.</li> </ul> </li> </ol> In Change_Point_Analysis you find the following files: <ol> <li>cp_probs...npy contain the joint probabilities of the corresponding change point configurations (The joint probabilities are saved corresponding to the order in which Python's itertools.combinations() creates the configurations. This holds also for the cp_probs_5_cps.npy for which the whole combinations array is not saved for memory reasons),</li> <li>cp_pdfs...npy contain the marginal probability density functions of the ordinal change point positions averaged over all configurations,</li> <li>cp_configs...npy contain the configurations,</li> <li>segment_fit...npy contain the segment fit data,</li> <li>segment_fit_variance...npy contain corresponding variances,</li> <li>In the case of five change points only the plotted 1st, 13th and 26th most probable configuration in config_ranking_CP1_5.npy for memory reasons.</li> <li>the data and results of figure 3 for each crisis event can be found in the corresponding directory's folders: <ul> <li>blue corresponds to the pre-crisis data segments,</li> <li>green corresponds to the data segments up to the green vertical dotted line,</li> <li>red corresponds to the longest data segments incorporating near and in-crisis data.</li> </ul> </li> </ol>

opencc-by-nc-4.0Mar 2023View details →

Supplementary data files for Manzano-Marín et. al. 2023 "Evolution of an alternative genetic code in the Providencia symbiont of the haematophagous leech Haementeria acuecueyetzin"

The data set consists of siz folders: 1) "genome_data": GenBank-formatted annotation files for newly sequenced Providencia siddallii endosymbionts. 2) "orthoMCL_data": Flat-text output files from the OrthoMCL pipeline. 3) "phylongey": MrBayes run files for Providencia spp. Bayesian phylogenetic inference. 4) "UGA_proteins_and_genes": FASTA-formatted alignments of UGA-containing protein-coding gene sequences from figure 3 and table 3. 5) "RepeatModeler_Prsiddallii": Log files for RepeatModeler runs of P. siddallii genomes. 6) "checkM2_Psiddallii": checkM2 input and output files for P. siddallii protein sets. 7) "breseq_runs": breseq output folders for variant calling on newly assembled genomes. 8) "GSAlign_Prsiddallii_GTOCOR": output files of variant calling using GSAlign between P. siddallii strain GTOCOR1 (sampled in 2015 and reported in Manzano-Marín et. al. 2015 GBE) and GTOCOR2 (sampled in 2019 and reported in the associated work).

opencc-by-4.0Jul 2023View details →

Supplementary Data to: "Quantifying sub-seasonal growth rate changes in fossil giant clams using wavelet transformation of daily Mg/Ca cycles" in Geochemistry, Geophysics, Geosystems

El/Ca data and high resolution images of 3 laser-ablation tracks on a fossil giant calm. The following Isotopes were monitored 11B, 23Na, 24Mg, 27Al, 43Ca, 88Sr, 89Y and 138Ba. The data was measured with laser-ablation inductively coupled plasma mass spectrometry (LA-ICPMS) using a 3 x 33 µm laser slit. El/Ca ratios were calibrated using NIST SRM 612 as bracketing external standard (Jochum et al., 2011) with updated Mg values from Evans & Müller (2018) and 43Ca as the internal standard; data quantification follows Longerich et al. (1996) and was performed using the software iolite 4 (Paton et al., 2011). For details see main text. References: Evans, D., & Müller, W. (2018). Automated Extraction of a Five-Year LA-ICP-MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long-Term Data Quality, Optimisation and Laser Cell Homogeneity. Geostandards and Geoanalytical Research, 42(2), 159–188. https://doi.org/10.1111/ggr.12204 Jochum, K. P., Weis, U., Stoll, B., Kuzmin, D., Yang, Q., Raczek, I., Jacob, D. E., Stracke, A., Birbaum, K., Frick, D. A., Günther, D., & Enzweiler, J. (2011). Determination of Reference Values for NIST SRM 610–617 Glasses Following ISO Guidelines. Geostandards and Geoanalytical Research, 35(4), 397–429. https://doi.org/10.1111/j.1751-908X.2011.00120.x Longerich, H. P., Jackson, S. E., & Günther, D. (1996). Inter-laboratory note. Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. Journal of Analytical Atomic Spectrometry, 11(9), 899–904. https://doi.org/10.1039/JA9961100899 Paton, C., Hellstrom, J., Paul, B., Woodhead, J., & Hergt, J. (2011). Iolite: Freeware for the visualisation and processing of mass spectrometric data. Journal of Analytical Atomic Spectrometry, 26(12), 2508–2518. https://doi.org/10.1039/C1JA10172B

Supplementary Material to 'Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria'

This folder contains the supplementary materials to reproduce the results, tables, and figures from the following publication submitted to the Hydrogeology Journal:  Kokimova A., Collenteur, R.A. & Birk, S. Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria.

Data, code, and supplementary materials for Pearman P. B., Broennimann, O., et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution

The repository contains several archives of digital materials that were used and/or produced in the analyses presented in Pearman, P. B. and Broennimann et al.  Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution, likely 2023.  These archives include (1) Supplementary Materials files ; (2) Data and code to generate country-level maps and plots; and (3) data and code to generate all maps of species and joint climate niche marginality, all in  G-zipped tar archives. Readme files are available in each archive to guide running of the scripts and identification of objects in the Supplementary Materials. Please see the paper for all co-authors names, and the methods, the results obtained, and discussion of their implications. This work is dedicated to the memory of our friend and colleague Michael Bruford (1963-2023).

Vaccination of poultry against highly pathogenic avian influenza – part 1. Available vaccines and vaccination strategies. Annex A–Supplementary information on ToR 1 data

Table A.1 - Available vaccines for HPAI in poultry. The table includes information on vaccine characteristics such as HA seed strain, vaccine dosage and administration route, target species, authorisation status, challenge strain, duration of immunity and source of information. Table A.2 - Challenge experiments. The table includes data extracted from 28 selected studies from literature on challenge experiments. The data was used to quantify VES, VEm, VEsh and VEs,sh for each vaccine assessed within each study. For each value of VEs,sh the probability Rvac < 1 was estimated to infer the probability of the vaccine to potentially stop transmission in vaccinated birds (VET). Table A.3 - Transmission experiments. The table includes data extracted from 12 studies from the literature, data was used from the unvaccinated and vaccinated groups to quantify VES, VEm, VEsh and VEs,sh for each vaccine assessed within each study; the estimated R values for the unvaccinated (Runv) and vaccinated (Rvac) groups were also extracted. The Rvac values were used to create a binomial variable classifying whether the vaccine could stop transmission (R < 1) or not.

Kinematic Evolution of the Tangra Yumco Rift, South-Central Tibet: Supplementary Data Tables

<h4>We investigate rifting during continental collision in southern Tibet by testing kinematic models for two classes of rifts: Tibetan rifts are defined as >150 km in length and crosscut the Lhasa Terrane, and Gangdese rifts are <150 km long and isolated within the high topography of the Gangdese Range. Discerning rift kinematics is a crucial step towards understanding rift behavior and evolution that has been historically limited. We evaluate spatiotemporal trends in fault displacement and extension onset in the Tangra Yumco (TYC) rift and several nearby Gangdese rifts, and examine how contraction and rift exhumation relate to evolution of the Gangdese drainage divide. Igneous U-Pb and zircon (U-Th)/He (ZHe) results indicate rift footwall crystallization between ~59-49 Ma and cooling between ~60-4 Ma, respectively, with ZHe ages correlating  with sample latitude. Samples from Gangdese latitudes (~29.4-29.8°N) yield predominantly Oligocene-early Miocene ages, whereas samples north of ~29.8°N yield both late Miocene-Pliocene ages and Paleocene-Eocene ages. Thermal history models indicate two-stage cooling, with initially slow cooling followed by accelerated cooling during late Miocene-Pliocene time. From spatial distributions of ZHe ages we interpret: (1) ~28-16 Ma ages from Gangdese latitudes reflect exhumation along contractional structures, (2) ~8-4 Ma ages reflect rift-related exhumation, and (3) ~60-48 Ma ages indicate these samples experienced lesser rift exhumation. Our data are consistent with a segment linkage evolution model for the TYC rift, withinteractions between rifts and contractional structures likely influencing the evolution of topography and location of the Gangdese drainage divide since Miocene time.</h4>

Supplementary data accompanying HOCOMOCO v12 collection of transcription factor binding motifs

*** SUMMARY ***This dataset contains supplementary data accompanying HOCOMOCO v12 collectionof DNA binding motifs for human and mouse transcription factors, https://hocomoco.autosome.org The contents include:- the complete initial set of motifs discovered from ChIP-Seq and HT-SELEX data;- the curated subset of motifs associated with distinct motif subtypes that were used in benchmarking;- the benchmarking results and the resulting final motif collections, including motif logos;- accompanying metadata. Please refer to the README and the HOCOMOCO website for further details.

opencc-by-4.0May 2023View details →

MultiBarcodeTools: Supplementary Data

Supplementary Data of MultiBarcodeTools.<ul><li>refDB_34_Primers_fish.tsv.gz: a reference database for amplicons of 34 fish eDNA metabarcoding primers predicted using <a href="https://doi.org/10.1111/1755-0998.13741">CRABS v0.1.3 (Jeunen et al., 2022)</a> by targeting 3,482 fish species with complete mitogenomes.</li><li>Minamoto_Simulate.tar.gz: taxonomy identification results from the standalone MiFish Pipeline on real and simulated data from samples from the Sagami River, Japan (<a href="https://doi.org/10.1371/journal.pone.0258073">Takasaki et al., 2021</a>).</li><li>Teleo_and_Riaz.tar.gz: taxonomy identification results from the standalone MiFish Pipeline on sequencing data from samples from the pond in Linkebeek, Belgium (<a href="https://doi.org/10.1111/mec.15742">Brys et al., 2021</a>).</li><li>refDB_19_Primers_insect.tsv.gz: a reference database for amplicons of 19 insect eDNA metabarcoding primers predicted using <a href="https://doi.org/10.1111/1755-0998.13741">CRABS v0.1.3 (Jeunen et al., 2022)</a> by targeting 4,484 insect species with complete mitogenomes. Note: three primers have no positive hits and are not included in the file.</li><li>refDB_3_Primers_fungi.tsv.gz: a reference database for amplicons of three fungal eDNA metabarcoding primers predicted using <a href="https://doi.org/10.1111/1755-0998.13741">CRABS v0.1.3 (Jeunen et al., 2022)</a> by targeting 14,615 fungal species with ITS reference sequences.</li><li>matrix.MultiBarcodePipeline.Result.Insect.xlsx: results produced by MultiBarcodePipeline using the command: multi-barcode refDB_19_Primers_insect.tsv -p cox1.mICOllintF_jgHC02198</li><li>matrix.MultiBarcodePipeline.Result.Fungi.xlsx: results produced by MultiBarcodePipeline using the command: multi-barcode refDB_3_Primers_fungi.tsv</li><li>msa.example.tar.gz: Full length sequences mentioned in Figure S5-S7</li></ul>

Supplementary data to 'The origin and differentiation of CO2-rich primary melts in Ocean Island volcanoes: Integrating 3D X-ray tomography with chemical microanalysis of olivine-hosted melt inclusions from Pico (Azores).'

Supplementary data to:<blockquote>The origin and differentiation of CO2-rich primary melts in Ocean Island volcanoes: Integrating 3D X-ray tomography with chemical microanalysis of olivine-hosted melt inclusions from Pico (Azores).</blockquote>