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1,773 results for “Supplementary data,”
Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry: Source and Supplementary Data
<p><em><strong>Source and Supplementary data for AANRI manuscript</strong></em></p>
Supplementary data files for Rogowska-van der Molen et. al. 2024 "From eggs to guts: Obligate association of Sodalis nezarae sp. nov. with the Southern green shield bug Nezara viridula"
<p>The data set consists of five directories:</p> <p><strong>1)</strong> "OrthoVenn3_run_Sodalis": Input and output files for a run of OrthoVenn3 using selected <em>Sodalis</em> spp.</p> <p><strong>2)</strong> "Sodalis_sp_Nvir_genome": GenBank-formatted annotation file for newly sequenced <em>Sodalis nezarae </em>endosymbiont, FASTA-formatted genomic assembly, and PseudoFinder input/output files.</p> <p><strong>3)</strong> "nutritional_genes_scan": FASTA-formatted files used for interrogating annotations for the presence of selected genes involved in the biosynthesis of essenatial amino acids, B vitmains, and other cofactors.</p> <p><strong>4)</strong> "phylogeny_Sodalis_spp": IQ-TREE2 run/result files for phylogenetic reconstruction of <em>Sodalis</em> spp. <em>sensu lato</em> using single-copy shared genes among selected genomes.</p> <p><strong>5)</strong> "Sodalis_sp_Nvir_species_det": FASTA-formatted and flat files for 16S and ANI identity/score calculations.</p> <p> </p>
Supplementary supply chain (input) data
<p>This document provides supplementary information on the Conference Paper entitled 'Ensuring supply for emergency services –<br>modeling supply chains with incomplete sets of data'' submitted by Kippenberger et al. for the Simulation Notes Europe (SNE)</p> <p> </p>
Supplementary data files of manuscript
Open the record for dataset details and reuse information.
Supplementary Data for Study on Strain Localization of Strike-Slip Fault Systems
<p>Point displacement measurements of fault slip from geodetic imaging and field surveying used to estimate off-fault deformation. </p>
Supplementary data for Development of Indicators of Social Vulnerability and Fishing Reliance in English Coastal Communities
<p>Supplementary data for Development of Indicators of Social Vulnerability and Fishing Reliance in English Coastal Communities by Tom Gibson, Chloe Lucas and Angela Muench. Full details are available via the publication and details of folder and file structures are available in the ReadMe file. </p>
Supplementary Data for A large-scale transcontinental river system crossed West Antarctica during the Eocene
<p>The file contains supplementary figures to the paper "A large-scale transcontinental river crossed West Antarctica during the Eocene", by Max Zundel, Cornelia Spiegel, Chris Mark, Ian Millar, David Chew, Johann Klages, Karsten Gohl, CD Hillenbrand, Yani Najman, Ulrich Salzmann, Werner Ehrmann, Jürgen Titschack, Thorsten Bauersachs, Gabi Uenzelmann-Neben, Torsten Bickert, Jule Müller, Frank Lisker, Steve Bohaty, Gerd Kuhn, and the Science Team of Polarstern Expedition PS104, published in Science Advances</p> <p><a name="_Hlk153790947"></a></p>
Supplementary data: Bayesian multi-exposure image fusion for robust high dynamic range ptychography
<p>Accompanying supplementary data for the paper. To download this data automatically and use the software, please refer to the details in the README of the linked github repository. </p> <p><strong>Github URL: </strong><a href="https://github.com/microscopic-image-analysis/bayes-mef"><strong>https://github.com/microscopic-image-analysis/bayes-mef</strong></a></p>
Supplementary files and data Files for "Discordance between mitochondrial, nuclear, and symbiont genomes in aphid phylogenetics: who is telling the truth?" Zoological journal of the Linnean society, 2024, vol 1, issue 4. https://doi.org/10.1093/zoolinnean/zlae098
<p>This repository comprises</p> <ul> <li>a file with all supplementary Tables (<strong>Supplementary_Tables</strong>). Table S1: Collection details and voucher ID for aphid samples from the CBGP-Inrae collection, data origin is given for other specimens. Table S2: Amplification success of long range DNA fragments from mitochondrial genomes . Table S3: Primers used for fluidigm aplification of nuclear genes and sequencing success. Table S4. Genomic features of newly sequenced Buchnera aphidicola with aphid taxonomic affiliation. Table S5: Summary of models used for each ML analysis and corresponding log-likelihood score of the best tree.Table S6: Output of RERConverge analyses.</li> <li>two Supplementary figures: Figure S1: Workflow of phylogenetic analyses as implemented on each dataset. Figure S2: Plot depicting the genome-wide pattern of molecular evolution (dN/dS) between disymbiotic (n = 15) and monosymbiotic aphid (n = 45) branches across the ML phylogeny (horizontal bars indicate 95% CI of the means). <em>P</em> value was calculated by using Wilcoxon Rank test.</li> <li>a word file (Text S1) with : Details of protocol for obtaining mitochondrial genomes through long-range DNA amplifications and Illumina sequencing, and two-step PCR protocole.</li> <li>an archive (archive1) with the mitochondrial AA and DNA matrices and alternative phylogenetic trees under ML and Bayesian analyses ; </li> </ul> <ul> <li>an archive (archive2) with the nuclear AA and DNA matrices and alternative phylogenetic trees under ML and Bayesian analyses</li> <li>an archive (archive 3) with the twelve new <em>Buchnera</em> genome drafts.</li> <li> an archive (archive4) with the <em>Buchnera</em> AA matrices and alternative topologies </li> </ul> <p> </p>
Supplementary data to article "From single trees to country-wide maps: Modeling mortality rates in Germany based on the Crown Condition Survey"
<p>This repository provides regression models and annual prediction rasters for tree mortality in Germany. </p> <p><strong>Regression models:</strong><br>Logistic regression models which predict tree mortality for the species (beech = Fagus sylvatica, <br>oak = Quercus petraea and robur, pine = Pinus sylvestris, spruce = Picea abies) and species <br>groups (OB = other broadleaves, OC = other conifers) based on observations of dead trees in the<br>German Crown Condition Survey (Waldzustandserhebung) and a set of environmental predictor <br>variables. The predictors come from the domains of climate (clim), site conditions (site, i.e. <br>topography, soil, land cover, deposition), tree age (age) and some models contain pairwise <br>interaction terms between predictors (inter). All models were fit in R and are represented as <br>objects of the class glm and stored in files of the type rds.</p> <p><strong>Prediction rasters:</strong><br>Spatial predictions of the mortality rate across Germany for each tree species and species group <br>and for each year from 1998 to 2022. The rasters have a spatial resolution of 100 m. Missing values<br>mark areas where the species/group does not occur. The mortality values are given as integers <br>between 0 (no mortality) and 10000 (100% mortality). The coordinate reference system is Lambert <br>Azimuthal Equal Area (LAEA; EPSG:3035). The rasters are provided in the file format GeoTIFF (tif).</p> <p>A detailed description of the data sources and analyses can be found in the following article.</p> <p><strong>Citation:</strong><br><em>Knapp, N., Wellbrock, N., Bielefeldt, J., Dühnelt, P., Hentschel, R., Bolte, A., 2024. </em><br><em>From single trees to country-wide maps: Modeling mortality rates in Germany based on the Crown Condition Survey.</em></p> <p><strong>Contact:</strong><br>nikolai.knapp@thuenen.de</p> <p> </p> <p> </p>
Supplementary methods and data for: Dogs with a vocabulary of object label remember labels for at least two years
<p>Long-term memory of words has a crucial role in the developing abilities of young children to acquire language. In dogs, the ability to learn object labels is present in only a small group of uniquely Gifted Word Learner (GWL) dogs. The ability of these dogs to acquire large vocabularies consisting of hundreds of names of dog toys through naturally occurring interactions in human families presents them as a valid model for studying language-related cognitive mechanisms. As they are very rare, little is known about the mechanisms through which they acquire such large vocabularies. In the current study, we tested the ability of five GWL dogs to retrieve 12 labelled objects two years after the object-label mapping acquisition. The dogs proved to remember the labels of between 3-9 objects. The results shed light on the process by which GWL dogs acquire an exceptionally large vocabulary of object names. As memory plays a crucial role in language development, these dogs supply a unique opportunity to study label retention in a non-linguistic species.</p>
Supplementary data: Effect of genotype by environment interaction (GEI) analysis for potato tuber yield and their quality traits in organic multi-environment domains of Poland
<p>Climate and raw data supplementary to the related publication in the journal Agriculture (ISSN 2077-0472).</p>
Sahana et al. Supplementary Data for Global Transboundary River Research: Databases, Case Study Analysis, and Regional Statistics for Sustainable Management
<p><span>This dataset supports our comprehensive review article on transboundary river research, exploring its implications for sustainable management worldwide. Utilizing machine learning, we analyzed 4,237 publications and conducted an in-depth desk review of 325 selected papers, examining a total of 4,713 case studies spanning 286 river basins globally. The study provides critical insights into upstream, midstream, and downstream regions, offering a complete view of challenges and opportunities in transboundary river management. Supplementary Data 1 contains the main database used in this study, sourced from Scopus, Web of Science, and Google Scholar. Additionally, Supplementary Data 2 and 3, included in the spreadsheet, offer statistics and further resources essential for understanding regional and cross-regional dynamics in river basin governance. These supplementary resources include key statistics, case study metadata, and tools, helping to facilitate a deeper exploration of basin-specific and global trends in transboundary water management. This collection of data and resources provides a valuable foundation for researchers and policymakers in advancing sustainable transboundary river management practices.</span></p>
MiCK_Supplementary_Data
<p>The dataset comprises all the Sequence files, Database data files, and Metadata files used for the development of the MiCK database.</p>
Supplementary Data for "Progressively smaller outbursts despite worldwide growth of glacier lakes"
<p>This respository contains the source data for the study for<em><strong> Progressively smaller outbursts despite worldwide growth of glacier lakes</strong></em> by Georg Veh and co-authors.</p> <p>We investigate trends in the size of glacier lake outburst floods (GLOFs) in 13 mountain regions on 4 continents between 1990 and 2023. We distinguish between moraine-and bedrock-dammed lakes on the one hand, and ice-dammed and supraglacial lakes on the other hand. We use Bayesian hierarchical models, implemented in the package <em>brms</em> in in the statistical programming software <em>R</em> to model temporal trends in the lake area prior to failure on different geographical levels. More information on these data, including detailed scripts to process them, are available at https://github.com/geveh/GLOFsize.</p> <p>We provide the following data:</p> <p><strong>1 The GLOF database</strong></p> <ul> <li><em>glofdatabase_2024_10_21.ods:</em> OpenOffice table with all reported GLOFs. Compiliation as of Oct 21, 2024.</li> <li><em>all_glofs_tibble.RDS: </em>R-object of all reported GLOFs in the global GLOF database; data are not trimmed to the period 1990-2023.</li> <li><em>la_sf.RDS: </em>R-object containing all GLOFs with mapped lake areas before the outburst in the period 1990-2023.</li> <li><em>reported_GLOFs.rds:</em> R-object containing a table of reported GLOFs in the period 1990-2023 with machine readable names of glaciers and lakes.</li> <li><em>reported_GLOFs_with_geometry.rds: </em>R-object containing a <em>simple features</em> (sf) object of reported GLOFs in the period 1990-2023 with machine readable names of glaciers and lakes.</li> </ul> <p>For a description of the parameters in these tables and R-objects, please visit: Lützow, N., Veh, G., & Korup, O. (2023). A global database of historic glacier lake outburst floods. Earth Syst. Sci. Data, 15, 2983–3000, https://doi.org/10.5194/essd-15-2983-2023</p> <p>The GLOF database, V4.1 is also available at: http://glofs.geoecology.uni-potsdam.de/</p> <p> </p> <p><strong>2 Regional extents of study regions</strong></p> <ul> <li><em>rgiO2_dissolved_outlines.shp</em>: Merged outlines of the RGI O2 according to the 13 study regions in ESRI shapefile format </li> <li><em>glacier_buffers_split_by_O2_no_fid_correct_FULLNAME_2.gpkg: </em>Regional 5-km buffers around glaciers with overlapping buffers removed in geopackage format.</li> </ul> <p> </p> <p><strong>3 Estimated glacier thickness data</strong></p> <ul> <li><em>RGI-wide_composites_stats_GV.txt:</em> Textfile of estimated glacier thickness for every glacier in the Randolph Glacier Inventory V6.0. Data were made available from Daniel Farinotti (personal communication).</li> <li><em>reg_invs_bind.rds: </em>A table of all glaciers in the 13 study region that had an estimate of average ice thickness.</li> </ul> <p> </p> <p><strong>4 Glacier lake data</strong></p> <p>We do not share raw data from previously lake inventories because they might be subject to different licenses. Please contact the authors directly if you would like to access these data. Here we share</p> <ul> <li><em>Glacier_lakes_global.ods: </em>OpenOffice spreadsheet of previously published glacier lake inventories, including reference to the underlying study, year, and satellite image used to map glacier lakes.</li> <li><em>lakes_gt_1km.gpkg: </em>A geopackage of all lakes >1km² as of 2015 or later, manually labelled with descriptors of their geometric properties obtained from interpreting high-resolution satellite images.</li> </ul>
Supplementary Data for "Epigenetic mechanisms controlling human leukemia stem cells and therapy resistance"
<p><strong>We performed functional genomic profiling of diverse leukemias using label tracing techniques. We identified AML stem cell quiescence is defined by distinct promoter-centered chromatin and gene expression dynamics, and controlled by a novel transcription factor network, which is associated with disease persistence and chemotherapy resistance in multiple patients. </strong></p>
Supplementary data for manuscript "Genetic risk converges on regulatory networks mediating early type 2 diabetes"
<p>Supplementary data for manuscript "Genetic risk converges on regulatory networks mediating early type 2 diabetes" Nature 624, 621–629 (2023). <a href="https://doi.org/10.1038/s41586-023-06693-2">https://doi.org/10.1038/s41586-023-06693-2</a></p> <p>Brief description of the included files is given below. Please visit the manuscript website for latest updates: <a href="http://theparkerlab.org/manuscripts/2021_islet-rfx6/">http://theparkerlab.org/manuscripts/2021_islet-rfx6/</a></p>
Supplementary data: The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia in a xenotransplantation model of Alzheimer's disease
<p>Supplementary data for: The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia in a xenotransplantation model of Alzheimer’s disease. </p> <p>Supplementary_Table1_QC: Excel sheet containing QC metrics for the RNA-seq data and the other containing QC metrics for the ATAC-seq data. </p> <p>Supplementary_Table2_DEGs: Excel sheet containing DeSeq2 differential expression analysis results for the following comparisons: APOE2 vs APOE3, APOE4 vs APOE3, APOE4 vs APOE2, APOE-KO vs APOE3. </p> <p>Supplementary_Table3_MAGMA_geneset_analysis_res: CSV file containing MAGMA gene set analysis results using the differentially expressed genes (FDR < 0.05) for the comparisons outlined in Supplementary_Table2_DEGs and three independent AD GWAS. </p> <p>Supplementary_Table4_DARs: Excel sheet containing DeSeq2 differential accessibility analysis results for the following comparisons: APOE2 vs APOE3, APOE4 vs APOE3, APOE4 vs APOE2, APOE-KO vs APOE3. </p> <p>Supplementary_Table5_sLDSC_res.csv: CSV file containing s-LDSC results using the consensus set of ATAC-seq peaks with three brain disorder GWAS (Alzheimer's disease, autism spectrum disorder, and amyotrophic lateral sclerosis). </p> <p>Supplementary_Table6_WGCNA_clusterProfiler_pathway_enrichment.csv: CSV file containing pathway enrichment results using two WGCNA-identified modules that were significantly upregulated in APOE2-expressing microglia. </p> <p>Supplementary_Table7_homer_motifEnrichment_res.xlsx: Excel sheet containing Homer motif enrichment analysis results using top 100 peaks with increased and decreased chromatin accessibility for APOE2 vs APOE3, APOE4 vs APOE3, and APOE4 vs APOE2.</p>
Supplementary material and data from: Cranial volume and palate length of cats, Felis spp., under domestication, hybridisation and in wild populations
<p>Reduced brain size, compared with wild individuals, is argued to be a key characteristic among domestic mammal species, and is often thought to be a component of the "domestication syndrome". However, brain size comparisons are often based on old, inaccessible literature and in some cases drew comparisons between domestic animals and wild species that are no longer thought to represent the true progenitor species of the domesticated variant in question. Here we set out to replicate results concerning cranial volumes in domestic cats that were published in the 1960s and 1970s and compared wildcats, domestic cats and their hybrids. In light of new research and ideas surrounding domestication and its effects on domestic animals a replication of these studies is highly relevant. Apart from replicating these studies we also present new data on palate length in Felis cat skulls.</p> <p>Here we provide all data (both new and old digitzed data) upon which we based the analysis discussed in this manuscript. We further provide a link to the code used in the analysis.</p>
Supplementary data for structure-conditioned amino-acid couplings
<p>This dataset contains supplementary data for the work "Structure-conditioned amino-acid couplings: how contact geometry affects pairwise sequence preferences" and includes two files: a spreadsheet listing the CASP models used for structure evaluation and an archived directory containing the structure and energy files that make up "DB200K", the main dataset of interaction motifs and their structure-conditioned energies used in the published work.</p> <p>The spreadsheet, "CASP-models.xlsx", lists the CASP round (9, 10, etc.), target name, model ID, and GDT_TS score for each model included in the structure evaluation experiment (see Fig. 7 in the published work). All information was collected from the CASP website, predictioncenter.org. See the "CASP model evaluation" section in the Methods section of the published work for more information.</p> <p>The archived directory, "DB200K.tar.gz", contains the structures and structure-conditioned energies of 200,002 inter-residue contact motifs. Each motif has a structure and set of structure-conditioned energies for each of the three motif sizes considered in the published work: 1x1, 3x3, and 5x5. For each motif of each size, there are two corresponding files, both indexed by the motif size, PDB ID, and position pair (chain and residue numbers according to the PDB file). One file is a PDB file containing the motif's structure and the other is a text-based file listing the 400 structure-conditioned energies of the motif's interacting residue pair. Each of the 400 energies is indexed by the pair of three-letter amino-acid codes it corresponds to. The residue positions in the PDB file match those listed in the energy file. For details on how this database's contacts were selected, see the "Contact database creation" section in the Methods section of the published work; for details on how these energies were computed, see the "Structure-conditioned potentials" section.</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.