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3,684 results for “extract”
NextClone and CloneDetective: An Integrated Nextflow Pipeline and R Package for Clonal Barcode Extraction and Quantification
<p>Raw FASTQ files for the DNA-seq data required to replicate the analyses presented at: https://phipsonlab.github.io/NextClone-analysis/.</p>
Dataset to manuscript Excitation's lifetime extracted from electron-photon (EELS-CL) nanosecond-scale temporal coincidences
<p>The datasets provided are raw data after the initial electron-photon temporal lists have been analyzed to determine the electron-photon pairs and their temporal delay. These lists are too long and not very meaningful to be provided in full.</p><p>The datasets were analyzed with the following Python libraries: Numpy 1.23.5, Matplotlib 3.6.2, Scipy 1.10.0, Hyperspy 1.7.3.</p><p>The provided jupyter notebooks were used to generate the figures in the manuscript.</p>
DSM: Deep Sequential Model for Complete Neuronal Morphology Representation and Feature Extraction
<p>This is an open-source repository for hosting codes and data files from research, "DSM: Deep Sequential Model for Complete Neuronal Morphology Representation and Feature Extraction". We also provided a web service based on our methods, please go to http://114.117.165.134:8501/.</p><p>(1)raw_dataset.zip: </p><ol><li>1,282 neuron reconstructions from SEU-Allen dataset;</li><li>1,002 neuron reconstructions from Janelia dataset;</li><li>1,100 neuron reconstructions from ION dataset.</li></ol><p>(2)Supplementary.zip: Supplementary information, including tables and figures;</p><p>(3)DSM-tools.zip: A python package for converting neuron morphology into sequences and implementing DSM models.</p><ol><li>NeuronSequenceDataset class: to transform SWC files to sequence dataframes by binary tree traversals, and prepare for the input of DSM networks.</li><li>DSMDataConverter class: a helper to convert the sequence dataframes for classification and clustering.</li><li>DSMHierarchicalAttentionNetwork class: classification model, giving a pre-trained DSM-HAN model by default.</li><li>DSMAutoencoder class: clustering model, giving a pre-trained DSM-AE model by default.</li></ol><p>(4)neuron2seq_for_developer.zip: A repository for further development of the models, including source codes and all data files.</p>
Dataset for the paper "TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution"
<p><strong>Dataset for the paper "TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution".</strong></p><p>We store values of the basic build-in Python types: numeric (int, float, and complex), boolean (bool), and text sequence (str). We also store values of the types: sequence (list, tuple, and range), set (frozenset and set), and mapping (dict) that include only basic types. To create the dataset, we monitored the test suites of 15 Python Standard Libraries. TestDossier contains 1,234 distinct argument/variable names and 133,169 dis- tinct values, leading to a total of 12,9M individual values.</p>
Model America - Arizona extract from ORNL's AutoBEM - (Archetypes with simulation results)
<p>Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>).</p> <p>Two sets of data are provided for 2,555,153 buildings located within the boundary of Arizona in the United States:</p> <ol> <li><strong>Data (420KB *.csv) - Arizona 527 building archetypes based on different Climate Zones (2B-136, 3B-133, 4B-128, 5B-130) with simulation results.</strong></li> <li><strong>Models (38.8MB *.zip by Climate Zone) – OpenStudio and EnergyPlus building energy models named according to ID.</strong></li> </ol> <p> </p> <p>This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).</p>
A dataset of 1600 images extracted from 5 cm RGB orthophotos for the classification of 12 classes of roofing materials
<p>This dataset contains a collection of 1601 image tiles of 64x64 pixels (3.2x3.2m²) annotated for 12 roofing materials. These tiles were extracted from 5 cm RGB orthophotos acquired by the city of Namur (Belgium) in 2017. The additional data used to create this dataset are (a) a Namur roof section mask, and (b) a set of 1601 material samples acquired using stratified random sampling. The tiles were obtained as follows: the centroid of each roof section containing a sample is used to extract tiles. A size of 64x64 pixels has been chosen so that a tile contains information for only one roof section, in order to learn only the colour and texture of the roof materials. This also avoids adding information outside the given roof section. The tiles are thus extracted for each orthophoto spectral band and labelled with the identifier of the class of roofing materials to which they belong. Here are the 12 material classes considered, preceded by their labels:</p> <p>0- Solar panels<br>1- Brown tiles<br>2- Orange tiles<br>3- Black tiles<br>4- Dark membranes<br>5- White membranes<br>6- Slates containing asbestos<br>7- Slates without asbestos<br>8- Corrugated asbestos-cement sheets<br>9- Gravel<br>10- Vegetation<br>12- Metals</p> <p>There are approximately 140 tiles by material class except for the vegetated roof sections (class 10) which contains only 47 samples due to its rarety.</p> <p>The dataset contains 1 folder for each spectral band. Each folder contains 1601 thumbnails in tif format named as follows:</p> <p><strong>img[tile id]_[class label].tif</strong></p> <p>It is suggested to apply pre-processing to these images as done by<a href="https://doi.org/10.1109/jurse57346.2023.10144142"> Wyard et al. (2023).</a></p>
A Deep Learning Approach to Extract Balanced Motions from Sea Surface Height Snapshot
<p>Related dataset for the paper "A Deep Learning Approach to Extract Balanced Motions from Sea Surface Height Snapshot" submitted to GRL</p>
Semantic Event Extraction Datasets
<p>Two datasets for Semantic Event Extraction that have been created using a distant labelling approach.</p> <p>They contain sentences from Wikipedia and events identified within them, their relations and attributes regarding the classes, properties and entities in the Wikidata and DBpedia knowledge graphs.</p>
Data for: A new threshold selection method for species distribution models with presence-only data: extracting the mutation point of the P/E curve by threshold regression
<p>Selecting thresholds to convert continuous predictions of species distribution models proves critical for many real-world applications and model assessments. Prevalent threshold selection methods for presence-only data require unproven pseudo-absence data or subjective researchers' decisions. This study proposes a new method, Boyce-Threshold Quantile Regression (BTQR), to determine thresholds objectively without pseudo-absence data. We summarize that the mutation point is a typical shape feature of the predicted-to-expected (P/E) curve after reviewing relevant articles. Analysis based on source-sink theory suggests that this mutation point may represent a transition in habitat types and serve as an appropriate threshold. Threshold regression is introduced to accurately locate the mutation point.</p> <p>To validate the effectiveness of BTQR, we used four virtual species of varying prevalence and a real species with reliable distribution data. Six different species distribution models were employed to generate continuous suitability predictions. BTQR and nine other traditional methods transformed these continuous outputs into binary results. Comparative experiments show that BTQR has advantages in terms of accuracy, applicability, and consistency over the existing methods.</p>
Carotenoid oil extraction efficiencies in the case of Nannochloropsis gaditana S4 strain
<p>Carotenoids and astaxanthin (Ax) Extraction efficiency achieved by oil extraction from Nannochloropsis gaditana S4 strain grown at A4F facilities. Carotenoids and astaxanthin concentration was determined by spectrophotometric analysis</p>
Automatic User Story Generation: A Comprehensive Systematic Literature Review - Data Extraction
<p>This document presents the data extraction performed for the Systematic Literature Review in Automatic User Story Generation.</p>
Cryo soft X-ray tomography of 5 microns thick slab extracted from C. elegans midbody region
<p>Samples of C. elegans <span>larvae of strain DM8005 </span>were high pressure frozen using the waffle method. Multiple <span>roughly </span>5 micron thick slabs spanning <span>an L2 larva</span> were extracted using <span>the Serial Lift-Out</span> technique, and placed on rectangular <span>mesh </span>grids. Soft X-ray tomography was performed on individual slabs using the SXT-100 soft x-ray microscope at SiriusXT. The data reveals label free internal structure of fully hydrated C. elegans tissue, annotating the worm volume and adding context to cryo electron tomography data. </p> <p>SXT data was acquired from -50° to +53° in 1° steps and reconstructed using Weighted Back Projection. A 32 nm objective zone plate was used. Data pixel size is 29 nm. </p>
Cryo soft X-ray tomography of 5 microns thick slab extracted from C. elegans anterior region
<p>Samples of C. elegans <span>larvae of strain DM8005 </span>were high pressure frozen using the waffle method. Multiple <span>roughly </span>5 micron thick slabs spanning <span>an L2 larva</span> were extracted using <span>the Serial Lift-Out</span> technique, and placed on rectangular <span>mesh </span>grids. Soft X-ray tomography was performed on individual slabs using the SXT-100 soft x-ray microscope at SiriusXT. The data reveals label free internal structure of fully hydrated C. elegans tissue, annotating the worm volume and adding context to cryo electron tomography data. </p> <p>SXT data was acquired from -50° to +53° in 1° steps and reconstructed using Weighted Back Projection. A 32 nm objective zone plate was used. Data pixel size is 29 nm. </p>
Supplementary Table 1-9 of the manuscript: Magmatic Cl-H2O contents, fluid extraction and porphyry fertility: Evidence from zircon and its apatite inclusions
<p><strong><span>Table DR1</span></strong><span> Major element composition of biotite from the three intrusions in the ZOF</span></p> <p><strong><span>Table DR2</span></strong><span> Laser Raman spectra and trace element compositions of zircon grains from the Cretaceous intrusions in the ZOF</span></p> <p><strong><span>Table DR3</span></strong><span> Major element composition of plagioclase grains from the Cretaceous intrusions in the ZOF</span></p> <p><strong><span>Table DR4</span></strong><span> Sr isotopic composition of the plagioclase from the Cretaceous intrusions in the ZOF</span></p> <p><strong><span>Table DR5</span></strong><span> Zircon Lu-Hf isotopic composition of the Sifang granodiorite, Luoboling granodiorite porphyry and Zhongliao granodiorite</span></p> <p><strong><span>Table DR6 </span></strong><span>Zircon water contents and O isotopic compositions by SIMS of the Cretaceous intrusions in the ZOF</span></p> <p><strong><span>Table DR7 </span></strong><span>Major and volatile element composition of the zircon-host apatite from the Cretaceous intrusions in the ZOF </span></p> <p><strong><span>Table DR8</span></strong><span> The top 20 best fitting runs</span></p> <p><strong><span>Table DR9</span></strong><span> Summarization of the salinity calculations</span></p>
Data from: Extraction and identification of a wide range of microplastic polymers in soil and compost
<p>Microplastic (MP) pollution is globally widespread, however their presence in soil systems is poorly understood due to complexity of soil and lack of standardised extraction methods. Datasets provided contain data from optimisation (recoveries) of MPs extraction protocol from soil and compost based on olive oil and density separation using zinc chloride, in case of low-density polyethylene and polyethylene terephthalate. Density separation was further used to extract five microplastic polymers (PET, PS, PE, PP and PVC), added to soil and compost at different concentrations, which is also included in the dataset. Additionally, identification data of extracted MPs from spiked soil and compost samples.</p>
Classification results extracted by the baseline RFSS+SI+GLCM and U-Net models.
<p>Selected indicative cases demonstrate (A) S2_12-12-20_16PCC_6, (B) S2_22-12-20_18QYF_0, (C) S2_27-1-19_16QED_14 and (D) S2_14-9-18_16PCC_13 patches on test set.</p>
Assessment of animal diseases caused by bacteria resistant to antimicrobials: Cattle- Appendix B: Excel file with all data extracted
<p>Information on all the full-text studies that were assessed, including the reason for exclusion for those that were excluded at the full-text screening and the data extracted from the included studies, can be consulted here. </p> <p>The extensive literature review was carried out by the University of Copenhagen under the contract OC/EFSA/ALPHA/2020/02 – LOT 1 (https://ted.europa.eu/udl?uri=TED:NOTICE:457654-2020:TEXT:EN:HTML)</p>
Title of Dataset: NMR metabolomic analysis of Drosophila head extracts: 2 genotypes (control, paraKO)
<p>Characterization of <em>para<sup>ko</sup></em> model in <em>Drosophila melanogaster</em> showed homeostasis disturbances as heat-induced phenotype, neuromuscular and cognitive alterations. Moreover, preliminary results during starvation assay revealed possibly differences in metabolism. To assess that NMR spectroscopy was made, comparing heads from young control and mutant flies.</p>
Simulated complex structures of the h-FBP21 tandem WW domain with proline-rich ligand extracted from SmB/B' core-splicing protein
<p>The tandem WW domain of the human formin-binding protein 21 (h-FBP21 tWW) consists of two WW domains separated by a flexible linker. It can bind target sequences in two different orientations and the flexibility of the linker additionally allows the two WW domains to adopt various relative orientations to each other. As consequence, the elucidation of possible complex structures for the h-FBP21 tWW is very challenging.</p> <p>Here, we present two complex structures for the h-FBP21 tWW and a proline-rich sequence from its natural binding partner, the core-splicing protein SmB/B’. Showing parallel (‘6’) and antiparallel (’14’) binding orientation, the two structures also differ in the relative positioning of the WW domains.</p> <p>For further instructions regarding the files, please refer to ‘README’.</p>
Supplementary Table S1 (raw data) of "Filtration extraction method using microfluidic channel for measuring environmental DNA "
<p>Supplementary Table S1 (all raw data) of "Filtration extraction method using microfluidic channel for measuring environmental DNA ". Each data of the validation experiment; Experiment 1-4 was located in different sheets..</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.