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1,773 results for “Supplementary data,”
Abu Hureyra, Syria, Part 2: Additional evidence supporting the catastrophic destruction of this prehistoric village by a cosmic airburst ∼12,800 years ago, SUPPLEMENTARY DATA
<p>This is the <strong>Supplementary Information</strong> (figures, text, and tables) for Moore et al. (2023) Abu Hureyra, Syria, Part 2: Additional evidence supporting the catastrophic destruction of this prehistoric village by a cosmic airburst ∼12,800 years ago. ScienceOpen 1.</p>
Supplementary data and material, Global strategy for the conservation and use of eggplants.
<p>Supplementary data and material from</p> <p>Solberg, S., van Zonneveld, M., Rakha, M. T. , Taher, D. I. , Prohens, J., Jarret, R. van Dooijeweert, W., and Peter Giovannini. 2022. Global strategy for the conservation and use of eggplants. Global Crop Diversity Trust. Bonn, Germany.</p>
Cell Health Data Supplementary Files
<p>This dataset contains supplementary files related to the <em><a href="https://github.com/WayScience/cell-health-data">cell-health-data</a></em> repository that were too large to upload on GitHub. Each of these files were saved to and loaded from an external hard drive during Cell Health Data Processing. These files include:</p> <ul> <li>single_cell_classification_probabilities/ : Single cell classification probabilities derived with each model trained in <a href="https://github.com/WayScience/phenotypic_profiling_model">phenotypic_profiling_model</a>. Each compressed csv file in single_cell_classification_probabilities/ corresponds to single-cell classifications from a particular plate as derived with a particular model. The model used to derive the probabilities is indicated by the file's parent folders. Each compressed csv file includes the metadata (location and perturbation) and phenotypic class probabilities for each cell in the plate.</li> <li>classification_profiles/ : This folder contains aggregated data known as "classification profiles". These profiles are generated from the single-cell classification probabilities found in the 'single_cell_classification_probabilities/' folder. Specifically, for each model, we find the mean of the single-cell classification probabilities across each perturbation and cell line to create a composite profile. This aggregated data provides a summarized view of cell behavior for each perturbation/cell line combination, as predicted by each model.</li> </ul> <p>For more information regarding the generation of this data, please see <a href="https://github.com/WayScience/cell-health-data/tree/master/4.classify-single-cell-phenotypes">cell-health-data/4.classify-single-cell-phenotypes</a>.</p>
Seq2science manuscript supplementary data
<p>Supplementary data for the seq2science manuscript.</p> <p>Includes a description on how to install seq2science, and for each re-analysis its configuration, samples file, and QC report.</p>
Supplementary data for: "The demographic history of the wild crop relative Brachypodium distachyon is shaped by distinct past and present ecological niches"
<p>Supplementary data to https://doi.org/10.1101/2023.06.01.543285</p>
Supplementary Data to: "Organic Phases in Bivalve (Arctica islandica) Shells: Their Bulk and Amino Acid Nitrogen Stable Isotope Compositions" in Geochemistry, Geophysics, Geosystems
<p>This dataset contains the data generated for publication "Organic Phases in Bivalve (<em>Arctica islandica</em>) Shells: Their Bulk and Amino Acid Nitrogen Stable Isotope Compositions", including the following files:</p> <p>Specimen_ID_shell_morphology_measurement: Description of locality of collection, shell ID, shell working ID and the shell morphology measurement which can be referred to Section 2.1 of the manuscript.</p> <p>EA_IRMS_raw_error_propagate: This file contains data showing the m/z 28 signal intensities of all measurements and the error propagation that mentioned in Section 2.3 of the manuscript. It also includes the calculation of analytical accuracy and precision. </p> <p>Statistics: The file contains the summary of statistical analyses performed in this manuscript. Refer to Section 2.7 and 3.3.</p> <p>Recovery: It contains the recovery of the total nitrogen contents or amino acid concentrations after different treatments and this was mentioned in Section 4.1 of the manucript.</p> <p>Mass_balance: The computation procedure that showed in Section 3.4 and discussed in Section 4.3 can be traced in this file.</p> <p>GC-C-IRMS_long_term_sd: The file shows the long-term precision of GC-C-IRMS computed from the mixed standard of amino acids </p> <p>BSIA_d15N: The file contains all the bulk d15N data that used in this manuscript.</p> <p>CSIA_d15N: The file contains all the amino acid d15N data that used in this manuscript.</p> <p>AA_Composition: The file shows AA percent data that used in this manuscript.</p> <p><br> For details see main text of the manuscript.</p> <p><br> </p>
Supplementary data for paper "Extreme mass-ratio inspiral and waveforms for a spinning body into a Kerr black hole via osculating geodesics and near-identity transformations"
<p>Radiation-reaction fluxes and NIT interpolant data for paper "Extreme mass-ratio inspiral and waveforms for a spinning body into a Kerr black hole via osculating geodesics and near-identity transformations"</p>
Supplementary data for Competition and Virulence in Pseudomonas syringae
<p><strong>Supplementary data 2.1.1</strong></p><p>CSV file describing 2,161 PSSC genomes used in the evaluation of PCR primers in chapter 2.1 and used as reference genomes for classification of isolates at syringae.org in chapter 2.2. file contains RefSeq accession numbers for each genome, T3E family repertoires, and phylogroup and ANI clusters assigned to each genome (metadata.csv) </p><p> </p><p><strong>Supplementary data 2.1.2</strong></p><p>Table describing columns contained in Supplementary data 2.1.1</p><p> </p><p><strong>Supplementary data 2.2</strong></p><p>Excel file with in-silico amplification rates for all 16 primer sets evaluated in chapter 2.1, both overall and by phylogroup.</p><p> </p><p><strong>Supplementary data 2.3</strong></p><p>Newick tree file containing the phylogenetic tree of 2,161 PSSC genomes used throughout chapters 2 and 3, with bootstrap values.</p><p> </p><p><strong>Supplementary data 2.4</strong></p><p>HMM file containing hidden Markov models for all VFOCs identified in chapter 2.1 and 2.2.</p><p> </p><p><strong>Supplementary data 2.5.1</strong></p><p>JSON file describing all canonical T3SS, T3E, and WHOP genes in the 2,161 genomes used in chapter 2.1 and 2.2, as detected by HMMER, with genome accessions as top-level keys. Additional keys found in each file are described in Table 2.2.3.</p><p> </p><p><strong>Supplementary data 2.5.2</strong></p><p>Table containing description of JSON structure for Supplementary data 2.5.1</p><p> </p><p><strong>Supplementary data 2.6.1</strong></p><p>JSON file describing all canonical T3SS, T3E, and WHOP genes in the 2,161 genomes used in chapter 2.1 and 2.2, as detected by HMMER, with protein accessions as top-level keys. Additional keys found in each file are described in Table 2.2.3.</p><p> </p><p><strong>Supplementary data 2.6.2</strong></p><p>Table containing description of JSON structure for Supplementary data 2.6.1</p><p> </p><p><strong>Supplementary data 2.7</strong></p><p>TSV file containing LIN numbers associated with each reference genome, used as input for training classifiers. </p><p> </p><p><strong>Supplementary data 2.8</strong></p><p>FASTA file containing in-silico amplicons generated from primer set CTS_Hwang, used as input for training a Naïve Bayes classifier.</p><p> </p><p><strong>Supplementary data 2.9</strong></p><p>FASTA file containing in-silico amplicons generated from primer set gapA_Hwang, used as input for training a Naïve Bayes classifier. </p><p> </p><p><strong>Supplementary data 2.10</strong></p><p>FASTA file containing in-silico amplicons generated from primer set gyrB_Hwang, used as input for training a Naïve Bayes classifier. </p><p> </p><p><strong>Supplementary data 2.11</strong></p><p>FASTA file containing in-silico amplicons generated from primer set pgi_Yan, used as input for training a Naïve Bayes classifier. </p><p> </p><p><strong>Supplementary data 2.12</strong></p><p>FASTA file containing in-silico amplicons generated from primer set rpoD_Hwang, used as input for training a Naïve Bayes classifier. </p><p> </p><p><strong>Supplementary data 2.13</strong></p><p>Naïve Bayes classifier for primer set CTS_Hwang</p><p> </p><p><strong>Supplementary data 2.14</strong></p><p>Naïve Bayes classifier for primer set gapA_Hwang</p><p> </p><p><strong>Supplementary data 2.15</strong></p><p>Naïve Bayes classifier for primer set gyrB_Hwang</p><p> </p><p><strong>Supplementary data 2.16</strong></p><p>Naïve Bayes classifier for primer set pgi_Yan</p><p> </p><p><strong>Supplementary data 2.17</strong></p><p>Naïve Bayes classifier for primer set rpoD_Hwang</p><p> </p><p><strong>Supplementary data 3.1</strong></p><p>HMM1, representing tailocin tail fibers associated with killing class 1</p><p> </p><p><strong>Supplementary data 3.2</strong></p><p>HMM2, representing tailocin tail fibers associated with killing class 2</p><p> </p><p><strong>Supplementary data 3.3</strong></p><p>HMM3, representing tailocin tail fibers from PSSC strain UB246</p><p> </p><p><strong>Supplementary data 3.4</strong></p><p>Amino acid sequence for WP_044313553.1, representative of type 1a tailocin-associated tail fiber used for protein structure prediction in Supplementary data 3.5</p><p> </p><p><strong>Supplementary data 3.5</strong></p><p>PDB file containing predicted structure of WP_044313553.1, representative of type 1a tailocin-associated tail fiber </p><p> </p><p><strong>Supplementary data 3.6</strong></p><p>Amino acid sequence for WP_122688044.1, representative of type 1b tailocin-associated tail fiber used for protein structure prediction in Supplementary data 3.7</p><p> </p><p><strong>Supplementary data 3.7</strong></p><p>PDB file containing predicted structure of WP_122688044.1, representative of type 1b tailocin-associated tail fiber</p><p> </p><p><strong>Supplementary data 3.8</strong></p><p>Amino acid sequence for WP_005768002.1, representative of type 2 tailocin-associated tail fiber used for protein structure prediction in Supplementary data 3.9</p><p> </p><p><strong>Supplementary data 3.9</strong></p><p>PDB file containing predicted structure of WP_005768002.1, representative of type 2 tailocin-associated tail fiber</p><p> </p><p><strong>Supplementary data 3.10</strong></p><p>Amino acid sequence for WP_024674765.1, representative of type 3 tailocin-associated tail fiber used for protein structure prediction in Supplementary data 311</p><p> </p><p><strong>Supplementary data 3.11</strong></p><p>PDB file containing predicted structure of WP_024674765.1, representative of type 3 tailocin-associated tail fiber</p><p> </p><p><strong>Supplementary data 3.12</strong></p><p>Amino acid sequence for WP_198721597.1, representative of RSA1-like prophage-associated tail fiber used for protein structure prediction in Supplementary data 3.13</p><p> </p><p><strong>Supplementary data 3.13</strong></p><p>PDB file containing predicted structure of WP_198721597.1, representative of RSA1-like prophage-associated tail fiber</p><p> </p><p><strong>Supplementary data 3.14</strong></p><p>CSV file containing HMM1 and HMM2 genomic screen results, with accession numbers and identities of tail fibers detected in each genome.</p><p> </p><p><strong>Supplementary data 3.15</strong></p><p>CSV file containing HMM3 genomic screen results, with copy number of tail fibers detected in each genome and the phylogroup the genome belongs to</p>
Supplementary Data for "Using AlphaFold and Experimental Structures for the Prediction of the Structure and Binding Affinities of GPCR Complexes via Induced Fit Docking and Free Energy Perturbation"
<p>Supplementary data for publication "Using AlphaFold and Experimental Structures for the Prediction of the Structure and Binding Affinities of GPCR Complexes via Induced Fit Docking and Free Energy Perturbation".</p><p>Includes:</p><ul><li>All input structures used in the the retrospective benchmark dataset as well as the (at most) 5 best scoring output models.</li><li>Input structures and output models for IFD-MD predictions of SSTR2, SSTR4, and SSTR5 complexes.</li><li>Output FEP+ maps (in fmp format) for SSTR2, SSTR4, and SSTR5 best models (representative runs shown in publication).</li></ul>
Supplementary data for "DNATCO v5.0: Integrated Web Platform for 3D Nucleic Acid Structure Analysis"
<p>Supplementary data for "DNATCO: efficient and accurate analysis of nucleic acid structures"</p> <p>The data in "dnatco.datmos.org_1ehz_4qvi_5hix.zip" contains the DNATCO-annotated extended mmCIF files, full validation reports and NtC-specific restraint files for the three example PDB structures (1ehz, 4qvi, and 5hix) is deposited.</p> <p>A snapshot of the core structure processing library source code from the https://github.com/cernylab/libLLKA repository is included in the "libLLKA-main.zip" file.</p> <p>The fully offline multi-platform CLI version of the dnatco.datmos.org using Node.js is provided in the "dnatco.zip" file</p>
Ediacaran metazoan fossils with siliceous skeletons from the Digermulen Peninsula of Arctic Norway – Supplementary Data
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Supplementary data to translate ages across humans and great apes
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Supplementary data from: Introgression across narrow contact zones shapes the genomic landscape of phylogenetic variation in an African bird clade
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Supplementary data from: Early vertebrate biomineralisation and eye structure determined by synchrotron X-ray analyses of Silurian jawless fish
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Supplementary data from: 2'-O-Galloylhyperin prevents tissue remodeling in thyroid eye disease: prospects as a thyrotropin receptor antagonist
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Supplementary data for: Outmigrating central valley Chinook Salmon
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Supplementary data from: Marine origins and freshwater radiations of the otophysan fishes
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Supplementary data: The molecular evolution of cancer associated genes in mammals
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Supplementary data from: A genetic assessment of natural barriers for isolating a proposed Greenback cutthroat trout reintroduction area
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Supplementary data for: From genomics to integrative taxonomy? The case study of Pocillopora corals
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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.