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1,773 results for “Supplementary data,”
Ecological niche modeling and first records from Namibia and Zimbabwe validate the amphi-equatorial distribution of Byrsinus pseudosyriacus (Hemiptera: Cydnidae) - Supplementary data
<p><em>Byrsinus pseudosyriacus (</em>Linnavuori, 1977), the most widely distributed Afrotropical species of the genus <em>Byrsinus</em> Fieber, 1860 known hitherto only from the Sudano-Eremian area is for the first time reported in two countries south of the Equator. The species potential distribution map was generated using the ecological niche modelling (ENM) methods that allowed this species to be regarded as amphi-equatorial in distribution<strong>.</strong></p>
Supplementary data for the article: Parental age does not influence offspring telomeres during early life in common gulls (Larus canus)
<p>R code and data for generating supplementary figures and tables for the article "Parental age does not influence offspring telomeres during early life in common gulls (Larus canus)"</p>
Informing antenna design for Global 21-cm experiments using a simulated Bayesian data analysis pipeline (supplementary data)
<p>These are the posterior files, foreground simulation data sets and chromaticity factor values used to produce the results for <a href="https://arxiv.org/abs/2106.10193">arXiv:2106.10193</a>.</p> <p>Plots of the fitted signal and residuals for each case are included, as is a plotting function to reproduce key figures.</p> <p>Naming conventions:</p> <ul> <li>f0: Centre frequency of the 21cm signal present in the simulated data</li> <li>A: Amplitude of the simulated 21cm signal present in the simulated data</li> <li>M_sig: Model being fit to the data includes a 21cm signal</li> <li>M_nosig: Model being fit to the data is a foreground only</li> </ul> <p>Software used:</p> <ul> <li><a href="https://github.com/PolyChord/PolyChordLite/tree/839292290a7747dbee82933bb9f7f955ac45c3ca">PolyChord</a></li> </ul> <p> </p>
Supplementary Data for "Organic matter preservation in ancient soils of Earth and Mars"
<p>Global compilation of organic carbon content (TOC) of paleosols (ancient soils) throughout the geological record on Earth.</p> <p> Pleistocene (1 Ma) to the Archean (3.7 Ga)!</p> <p> </p>
Supplementary Material for Frontiers Plant Genetics and Genomics 'Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality'
<p>Authors</p> <p>Zhian N. Kamvar, Jonah C. Brooks, and Niklaus J. Grünwald</p>
Supplementary Material Douglas-fir data
<p>Supplementary information of the three Douglas-fir trials, family numbers, and pedigree data including identity information of trees, fathers, and mothers of the paper entitled: <strong>Identification and joint modeling of competition effects and environmental heterogeneity in three Douglas-fir (<em>Pseudotsuga menziesii</em> var. <em>menziesii</em>) trials.</strong></p>
Supplementary material 1: Number of Pteridaceae species by gender in Togo from: The Pteridaceae family diversity in Togo - Biodiversity Data Journal 3: e5078 (15 July 2015) https://doi.org/10.3897/BDJ.3.e5078
Number of Pteridaceae species by gender in Togo
Supplementary material 17: Generating Interactive Dashboard Charts Based on Plazi Treatment Data from: Integrating and visualizing primary data from prospective and legacy taxonomic literature - Biodiversity Data Journal 3: e5063 (12 May 2015) https://doi.org/10.3897/BDJ.3.e5063
A brief explanation of how to create and customize interactive charts using data on Plazi.
Supplementary material 3: List of tested and analyzed data sharing tools (non-exhaustive) from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
List of tested and analyzed data sharing tools (non-exhaustive)
Supplementary material 2: Definitions and Concepts from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
Definitions and concepts in the context of the main paper.
Supplementary material 1: List of selected tools. from: Data sharing tools adopted by the European Biodiversity Observation Network Project - Research Ideas and Outcomes 2: e9390 (31 May 2016) https://doi.org/10.3897/rio.2.e9390
List of selected tools.
Supplementary file pwt: Female length of Tylorida striata per taxonomic reference, examined syntypes and specimens from India from Bridging the distributional gap of Tylorida striata (Thorell, 1877) and new synonymy (Araneae: Tetragnathidae) - Biodiversity Data Journal 3: e4878 (26 March 2015) https://doi.org/10.3897/BDJ.3.e4878
Female length of Tylorida striata per taxonomic reference, examined syntypes and specimens from India
Supplementary file pwt: Collection sites for black flies from Turkish Thrace, 2002–2006. from Black flies (Diptera: Simuliidae) of Turkish Thrace, with a new record for Turkey - Biodiversity Data Journal 3: e4834 (22 April 2015) https://doi.org/10.3897/BDJ.3.e4834
Collection sites for black flies from Turkish Thrace, 2002–2006.
Supplementary material 2: Seu Nico Community Dynamics from: Tree Diversity and Dynamics of the Forest of Seu Nico, Viçosa, Minas Gerais, Brazil - Biodiversity Data Journal 3: e5425 (31 July 2015) https://doi.org/10.3897/BDJ.3.e5425
2868 tree occurrences from two census within 100 plots of 10x10 m in the Forest of Seu Nico (FSN), Viçosa municipality, Minas Gerais, Brazil, including measurements of each tree as well as environmental data from all 100 plots. Dataset consists of seven independent files
Supplementary data PhD thesis "Biogeography of West African Gallery Forests"
<p>The data sets uploaded in this repository are the raw data and supplementary material for the analyses in the PhD thesis as cited in the text. Specifically, the uploaded folders contain 1) Presence/absence matrix of AFLP markers from 4 gallery forest tree species (<em>Anogeissus leiocarpa, Diospyros mespiliformis, Paullinia pinnata, Pterocarpus santalinoides</em>); 2) Detailed results (the .xml input files and the.kml output files) for the BEAST species tree diffusion model of the markers from 1); and 3) Output results for MaxEnt distribution models of 20 gallery forest tree species. For details, methods and discussion see the PhD thesis.</p>
Supplementary Data: The Benefits of Cooperation in a Highly Renewable European Electricity Network
<p>Supplementary Data</p> <p><em>The Benefits of Cooperation in a Highly Renewable European Electricity Network</em><br> <em>doi:10.1016/j.energy.2017.06.004</em><br> <em>arXiv:1704.05492</em></p> <p>The files in this record contain the model-specific code, input data, and output data considered in the Benefits of Cooperation paper.</p> <p>You are welcome to use the provided data under the given open-source licence, and if you do please cite the paper <em>doi:10.1016/j.energy.2017.06.004</em>.<br> Please note that the derivation of the data in data/renewables/ is not open, because it uses the REatlas software [7] which has a closed source server part. (There is an free software implementation of the REatlas at https://github.com/FRESNA/atlite but it wasn't ready in time to be used for this dataset.)</p> <p>The code that is required to generate the output data consists of</p> <ul> <li>the python code opt_ws_network.py that builds and runs the PyPSA [0] model</li> <li>a SLURM script parameter_batch.py to run the model with different parameters</li> <li>a YAML file options.yml with the default parameter settings</li> </ul> <p>The code heavily relies on the python package <em>vresutils</em> which is available at https://github.com/FRESNA/vresutils</p> <p>The record also contains the input data in the data/ directory. They are described in detail in the paper, but a short summary is provided here:</p> <ul> <li><strong>costs</strong>: cost and other input parameter assumptions, see <em>Table 1</em> in the paper.</li> <li><strong>graph</strong>: the network topology is given by a list of nodes (country names) and a list of edges connecting two nodes. Based on [1,2].</li> <li><strong>hydro</strong>: hydro generation data provided by the Restore2050 project [3] <ul> <li>inflow/: contains a csv files with daily inflow data for each country</li> <li>emil_hydro_capas.csv: country-scale power and energy capacity</li> <li>ror_ENTSOe_Restore2050.csv: the share of run-of-river of the total hydro generation, from ENTSO-E [4] or if unavailable from [3]</li> </ul> </li> <li><strong>load</strong>: hourly country-scale consumption for 2011 from ENTSO-E [5]</li> <li><strong>renewables</strong>: generation potentials for the renewable technologies onshore wind, offshore wind, and solar per country based on historic weather data [6]. The jupyter-notebook europe_renewables_potentials.ipynb describes the data generation and uses the REatlas software [7] which has open-source client but closed-source server software. The used cutout can therefore not be made available here, but is solely based on data from [8]. The processed data are in: <ul> <li>store_p_nom_max/: installation potential per technology per region</li> <li>store_o_max_pu_betas/: hourly maximum generation per unit of capacity per technology per region</li> </ul> </li> </ul> <p>The output data generated by the model is in sub-folders of the results/ directory following the naming scheme [costsource]-CO[CO2costs]-T[timerange]-[technologies]-LV[linevolume]_c[crossover]_base_[costsource]_solar1_7_[formulation]-[startdate]/, where</p> <ul> <li>costsource = diw2030</li> <li>CO2costs = 0</li> <li>timerange = 1_8761</li> <li>technologies = wWsgrpHb</li> <li>linevolume = [float], None (line volume constraint of float * 5e8 TWkm, or optimised line volume)</li> <li>crossover = 0 (deactivated the cross-over phase of the Gurobi optimiser)</li> <li>formulation = angles, [blank] (power flow formulations: 'angles', or 'cycles')</li> <li>startdate = time the optimisation was started</li> </ul> <p>Footnotes</p> <p>[0] https://pypsa.org/ , https://doi.org/10.5281/zenodo.582307</p> <p>[1] S Becker, Transmission grid extensions in renewable electricity systems, PhD thesis (2015)</p> <p>[2] ENTSO-E, Indicative values for Net Transfer Capacities (NTC) in Continental Europe. European Transmission System Operators, 2011, https://www.entsoe.eu/publications/market-reports/ntc-values/ntc-matrix/Pages/default.aspx, accessed Jul 2014.</p> <p>[3] A Kies, K Chattopadhyay, L von Bremen, E Lorenz, D Heinemann, Simulation of renewable feed-in for power system studies, RESTORE 2050 project report, https://doi.org/10.5281/zenodo.804244</p> <p>[4] European Transmission System Operators, Installed Capacity per Production Type in 2015, ENTSO-E (2016), https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show</p> <p>[5] https://www.entsoe.eu/db-query/country-packages/production-consumption-exchange-package</p> <p>[6] D. Heide, M. Greiner, L. Von Bremen, C. Hoffmann, Reduced storage and balancing needs in a fully renewable European power system with excess wind and solar power generation, Renewable Energy 36 (9) (2011) 2515–2523. https://doi.org/10.1016/j.renene.2011.02.009</p> <p>[7] G. B. Andresen, A. A. Søndergaard, M. Greiner, Validation of Danish wind time series from a new global renewable energy atlas for energy system analysis, Energy 93, Part 1 (2015) 1074 – 1088. https://doi.org/10.1016/j.energy.2015.09.071</p> <p>[8] S Saha et al., 2014: The NCEP Climate Forecast System Version 2. J. Climate, 27, 2185–2208, https://doi.org/10.1175/JCLI-D-12-00823.1</p>
Supplementary Data: Raw interview data and NVivo11 analysis summary
<p>Interview data on a sample of software startups focusing on the early stages of their evolution paths.</p> <p>Summary of qualitative analysis of the data done with NVivo11 in a study focusing on the software startups from the viewpoints of resource-based-view and human capital theories. Human captital, defined as one type of resources in resource-based-view theory, is defined in existing research broadly as a set of capabilities, knowledge, skills, education, experience, and other similar human attributes, and seen as a source of economic growth at all levels from an individual to nations and the world.The qualitative analysis of the interview data was done to answer the following research questions: 1) What are the engineering-related capabilities necessary for creating a product in a software startup?, 2) What are the means to acquire the necessary capabilities?, and 3) What are the reasons for deploying different capability-acquiring means?</p> <p>The findings of the analysis were used for drawing conclusions, how the established theories, resource-based-view and human capital theories, fit to the actual situations in software startups.</p>
Supplementary data for ENACT: End-to-End Analysis and Cell Type Annotation for Visium High Definition (HD) Slides
<p>This project contains the datasets used to evaluate and reproduce the results of ENACT (End-to-End Analysis and Cell Type<br>Annotation for Visium HD Slides). The dataset consists of:</p> <ul> <li>a sample Visium HD sample of human colorectal cancer, courtesy of 10X Genomics (<a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-libraries-of-human-crc">Visium HD Spatial Gene Expression Library, Human Colorectal Cancer (FFPE) - 10x Genomics</a>). All credit goes to 10X Genomics.</li> <li>configuration files to be used to reproduce the results provided in the ENACT publication, </li> <li>evaluation plots used in the ENACT publication, and</li> <li>results obtained after running ENACT on the human colorectal cancer sample using the four bin-to-cell assignment methods (naive, weighted_by_area, weighted_by_transcript, and weighted_by_cluster) and the three cell annotation methods (Sargent, CellAssign, CellTypist)</li> </ul> <p>Additionally, results from running ENACT on the following three public VisiumHD samples are provided to showcase ENACT’s tissue-agnostic nature:</p> <div> <div> <div> <ul> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-lung-cancer-post-xenium-expt">Human Lung FFPE</a> sample from a subject with Adenocarcinoma (age and gender unspecified),</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-tonsil-fresh-frozen">Human Tonsil Fresh Frozen</a> sample from a 21 year old male subject with Reactive Follicular Hyperplasia,</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-breast-cancer-fresh-frozen">Human Breast Fresh Frozen</a> sample from a 58 year old female subject with Ductal Carcinoma in Situ (DCIS).</p> </li> </ul> </div> </div> </div> <p> </p>
Single Cell RNA Transcriptomics of Mantle Cell Lymphoma Reveals the Presence of Treatment-Resistant Subclones at the Time of Diagnosis - Supplementary Data
<p><strong>Supplementary Table 4.</strong> Results of optical genomic mapping for patient P009. The table lists genomic aberrations shared for diagnosis and relapse and those exclusive at both timepoints.</p> <p><strong>Supplementary Table 5.</strong> <strong>Sheet A:</strong> Results of differential gene expression analysis between relapse and diagnosis MCL cells of four patients (P009, P022, P027 and P087) performed using Wilcoxon rank-sum test. Only genes with adjusted p-value < 0.01, absolute log2 fold change > 1, and expression in at least 25% of cells in the upregulated group are included. <strong>Sheet B: </strong>Results of GO biological process enrichment analysis performed using clusterProfiler on upregulated and downregulated genes from each patient comparison. Multiple testing correction was performed using the Benjamini-Hochberg method. Only terms with q-value < 0.01 are shown.</p> <p><strong>Supplementary Table 6.</strong> Proportions of cells at four cell cycle phases (G0, G1, S, and G2M) at diagnosis (DG) and their changes after relapse (REL) in four aggressive MCL patients. Statistical analysis was performed using chi-square test.</p> <p><strong>Supplementary Table 7. </strong>Characterization of lymphoma sub-clones detected using CNV inference. <strong>Sheet A: </strong>Cell counts and proportions (prop) relative to total MCL cells in each subclone at diagnosis (DG) and relapse (REL). prop_FC – proportion fold change at relapse compared to diagnosis (calculated as prop_REL/prop_DG for expanding clones, or prop_DG/prop_REL for contracting clones). Subclone labels indicate putative treatment sensitivity: "Sens" denotes subclones that contracted or disappeared at relapse (suggesting chemotherapy sensitivity), while "Res" denotes subclones that expanded at relapse (suggesting chemotherapy resistance). <strong>Sheet B:</strong> CNV profiles of MCL subclones identified through inferCNV analysis. Each row specifies chromosomal coordinates (chr, start, end), copy number state (cn), cytogenetic location (cytobands), and genes within altered regions. Copy number states: cn=1 (deletion), cn=2 (normal), cn=3+ (amplification).</p> <p><strong>Supplementary Table 8.</strong> Differential gene expression analysis between resistant and sensitive MCL subclones. <strong>Sheet A:</strong> Summary of pairwise subclone comparisons. For each comparison between resistant (Res) and sensitive (Sens) subclones, the table reports counts of total, upregulated and downregulated differentially expressed genes and their ratio, enriched Gene Ontology (GO) terms and Hallmark gene sets in each direction. <strong>Sheet B:</strong> Complete list of differentially expressed genes from all pairwise subclone comparisons. Each row represents a single gene with statistical metrics including p-value, adjusted p-value, average log2 fold change (avg_log2FC), expression percentages in each subclone (pct.1, pct.2), regulatory direction (up/down), and gene description. <strong>Sheet C:</strong> Gene Ontology (GO) enrichment analysis results for differentially expressed genes. Only significantly enriched (q-value < 0.05) biological processes are shown with enrichment statistics including gene ratio, background ratio, fold enrichment, z-score, adjusted p-values, and lists of genes contributing to each enriched term. <strong>Sheet D: </strong>Hallmark gene set enrichment analysis (GSEA) results identifying coordinated expression programs differentially active between resistant and sensitive subclones. Results include normalized enrichment scores (NES), statistical significance, leading edge metrics, and core enrichment genes for each pathway.</p> <p><strong>Supplementary Table 9.</strong> Somatic variants in P069 samples. The variants were identified using a consensus approach integrating three variant callers (Mutect2, VarScan2, and Strelka2) and filtered using SomaticSeq with a PASS threshold score of 0.5. The table includes sample identifiers, genomic coordinates (hg38), variant allele frequencies (VAF) and genotypes (GT) for matched normal and tumor samples, sequencing depth (DP), and comprehensive functional annotations generated by Funcotator using GENCODE and HGNC databases. Key annotation fields include gene symbols, variant classifications, transcript information, protein changes, and gene ontology details. Only variants passing consensus filtering criteria with VAF ≥1% for heterozygous and ≥85% for homozygous calls are included.</p> <p><strong>Supplementary Data Object 1. </strong>SingleCellExperiment object with 57751 cells post-QC and 36601 genes. Data columns include sample, patient, timepoint, compartment, cell type annotation (cell_type_manual), cell cycle phase (tricyclePhase), tumor subclones (subclone_label).</p>
Supplementary Data for "Comparison of Ensemble-Based Data Assimilation Methods for Sparse Oceanographic Data"
<p>This data set represents the supplementary data for the paper Comparison of Ensemble-Based Data Assimilation Methods for Sparse Oceanographic Data (Section 4) by Florian Beiser, Håvard Heitlo Holm, and Jo Eidsvik.</p><p>It contains the data that is plotted in the manuscript. The code for plotting is provided in the supplementary software.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.