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9,113 results for “Sampling”
MetaBAT 2.12.1 genome binning of the CAMI 2 Mouse Gut Toy data set, samples 0-63, gold standard pooled assembly
Genome binning of the gold standard pooled assembly <br><strong>Software: </strong>MetaBAT<br><strong>SoftwareVersion: </strong>2.12.1<br><strong>DataURL: </strong> https://data.cami-challenge.org/participate<br><strong>SoftwareURL:</strong> https://bitbucket.org/berkeleylab/metabat<br><strong>ShortReadsUsed:</strong> True<br><strong>LongReadsUsed:</strong> False<br><strong>CommandUsed:</strong> bowtie2-build anonymous_gsa_pooled.fasta anonymous_gsa_pooled.fasta<br>for i in {0..63}; do bowtie2 -q --threads 30 --fr -x anonymous_gsa_pooled.fasta --interleaved sample_${i}/anonymous_reads.fq -S anonymous_reads_sample_${i}.sam ; done<br>for i in {0..63}; do samtools view -b sample_${i}.sam -o anonymous_reads_sample_${i}.bam & done<br>for i in {0..63}; do samtools sort anonymous_reads_sample_${i}.bam -o anonymous_reads_sample_${i}.sorted.bam ; done<br>for i in {0..63}; do samtools index anonymous_reads_sample_${i}.sorted.bam ; done<br>runMetaBat.sh -l anonymous_gsa_pooled.fasta anonymous_reads_sample_*.sorted.bam
Fig. 1. Ubatiba stream system showing all the four sampling sites. P1 in Fish movement in an Atlantic Forest stream
Fig. 1. Ubatiba stream system showing all the four sampling sites. P1 is the most upstream site and P4 is the most downstream site.
Fig 4 in Do different sampling designs produce differences in the metrics of curimba, Prochilodus lineatus (Characiformes: Prochilodontidae)?
Fig 4. Frequency distribution by standard length (SL) class of curimba for fixed and variable sampling sites in Volta Grande (VGR) and Jaguara (JR) reservoirs.
Fig. 3 in Do different sampling designs produce differences in the metrics of curimba, Prochilodus lineatus (Characiformes: Prochilodontidae)?
Fig. 3. Temporal variation in catch per unit effort (CPUE) of curimba for fixed and variable sampling sites in Volta Gran- de (VGR) and Jaguara (JR) reservoirs.
Large Uniform Random SAT Samples
<p>Large Random SAT samples generated with the following <em>samplers</em>:</p> <ul> <li>BDDSampler</li> <li>Spur</li> <li>QuickSampler </li> <li>KUS</li> <li>Unigen2</li> <li>Smarch </li> </ul>
IODP Expedition 362 Sample report
<p>Report includes detailed information about samples taken for testing: location/depth, type/form factor, test, request number, and database identifier.</p>
Fig. 24. Brembodus ridens Tintori, 1980. Sample CLC J-420. Small scales forming a in Osteology and relationships of Acrorhinichthys poyatoi gen. et sp. nov. (Pycnodontiformes) from the marine Late Cretaceous of Lebanon
Fig. 24. Brembodus ridens Tintori, 1980. Sample CLC J-420. Small scales forming a mosaic surrounding the cloaca.
Fig. 23. Brembodus ridens Tintori, 1980. Sample CLC J-420. A in Osteology and relationships of Acrorhinichthys poyatoi gen. et sp. nov. (Pycnodontiformes) from the marine Late Cretaceous of Lebanon
Fig. 23. Brembodus ridens Tintori, 1980. Sample CLC J-420. A. Scale of the dorsal region. B. Scale of the ventral region.
The SV callsets of the HG002 human sample produced by cuteSV with multi long-read sequencing platforms.
<p>The SV callsets of the HG002 human sample produced by cuteSV with multi long-read sequencing platforms.</p>
Appendix List of samples of deep frozen frog legs with purchase date, collection number, haplotype number, taxonomic identification, tibia length (TL) and estimated snout vent length (SVL). in Which frog's legs do froggies eat? The use of DNA barcoding for identification of deep frozen frog legs (Dicroglossidae, Amphibia) commercialized in France
Appendix List of samples of deep frozen frog legs with purchase date, collection number, haplotype number, taxonomic identification, tibia length (TL) and estimated snout vent length (SVL).
Phytoplankton pigment concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains phytoplankton pigment concentrations sampled during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3 and analysed using high performance liquid chromatography. Water samples were collected from the underway seawater supply every 3 hours and at multiple depths from select CTD (conductivity, temperature and depth) rosette deployments. Pigment concentrations have been quality controlled. This circumpolar dataset contains the main pigment concentrations of phytoplankton and can be used to infer phytoplankton biomass and class composition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_phytoplankton_pigments_20200511CURRSGCMR.csv, data file, comma-separated values</li> <li>ace_phytoplankton_pigments_lod.csv, metadata, comma-separated values</li> <li>ace_phytoplankton_pigment_concentrations_change_log.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p>Pigment concentration values below the limit of detection are reported with fill value ‘NaN’. Any null values are reported with fill value ‘NaN’.</p> <p><strong>Change log</strong></p> <p><strong>v1.1</strong><br> - Added statement to ReadMe in original data collection statement acknowledging analysis performed by Celine Dimier<br> - Added statement to Acknowledgements section of DOI acknowledging analysis performed by Celine Dimier<br> - Metadata for samples have been updated: AT/ACE/2/1/28/1026/DA/13 A_C07N17 and AT/ACE/1/1/14/402/DA/10<br> - Corrected ship name to R/V Akademik Tryoshnikov<br> - Corrected citation DOI for one minute cruise track</p> <p><strong>v1.0 </strong><br> - Initial release of phytoplankton pigment concentration dataset.</p>
Fig. 2. Sampling localities. A in Glossostyles perspicua gen. et sp. nov. and other fungivorous Cecidomyiidae (Diptera) new to the Czech and Slovak Republics
Fig. 2. Sampling localities. A. Velká Kotlina Glacial Cirque (Czech Republic) with a Malaise trap used in 2006. Frequent avalanches are the main cause of the unique subalpine biodiversity of this locality (e.g., more than 350 species of vascular plants have been recorded from there) B. Hrončecký grúň Reserve in Poľana Mts (Slovak Republic) with a Malaise trap used in 2005. This is a virgin forest mainly composed of fir and beech intermixed with ash, spruce and sycamore maple and with an enormous and unique diversity of flies (see Roháček & Ševčík 2009). Photos by J. Ševčík
Fig. 1. Sampling localities. A in Glossostyles perspicua gen. et sp. nov. and other fungivorous Cecidomyiidae (Diptera) new to the Czech and Slovak Republics
Fig. 1. Sampling localities. A. Rejvíz peat-bog (Czech Republic) with a Malaise trap used in 2004. A well preserved postglacial peat-bog with Pinus rotundata growth. B. Rejvíz peat-bog with the Malaise trap used in 2005. Photos by J. Ševčík.
Fig. 1. Sampling sites. A in Taxonomy and morphology of four "ophrys-related" scuticociliates (Protista, Ciliophora, Scuticociliatia), with the description of a new genus, Paramesanophrys gen. nov.
Fig. 1. Sampling sites. A. Coastal waters of the Yellow Sea at Qingdao, Shandong province. B. A coastal mariculture-region in Zhanjiang, Guangdong province. C. Coastal waters of Daya Bay, Guangdong province.
Rt-Cloud Sample Project 'AmygActivation' DICOM Data
<p>This upload contains the same data as published in <a href="https://doi.org/10.5281/zenodo.3677090">our previous zenodo dataset upload</a>. Unlike our previous upload, this version contains data after transferring the DICOMs directly from the Siemens Skyra 3T to our Linux machine (as done in real-time experiments). The purpose of this separate upload is to serve as sample data for our <a href="https://github.com/brainiak/rt-cloud">real-time cloud software</a>, for a <a href="https://github.com/amennen/amygActivation">specific sample project</a>. The brain data are contributed by author S.A.N. and are authorized for non-anonymized distribution.</p>
Dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) Legs 1-3. Water samples were collected from the underway seawater supply every 3 hours, preserved and analysed for dissolved inorganic nutrient concentrations using flow injection and colorimetric methods. These samples provide an estimate of the dissolved concentrations of inorganic macronutrients essential for phytoplankton growth.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_nutrients_20200527CURRSGCMR.csv, data file, comma-separated values</li> <li>change_log.txt, metadata, text</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - changed order of authors in publication and citation in README</p> <p>v1.0 - initial release of dataset</p>
The Set Increment with Limited Views Encoding Ratio (SILVER) Method for Optimizing Radial Sampling of Dynamic MRI: Supporting Data
<p>This data was created to perform the first experiments with the SILVER method of optimizing radial MRI acquisition. The files are mainly .mat files containing the numerical data used to assess the SILVER method using MATLAB (Version R2018b). Instructions on how to use the data and how to reproduce the experiments are available on https://github.com/SophieSchau/SILVER</p>
Covid-19 Twitter Database: Turkish Sample
<p>This dataset is a comprehensive dataset that includes Turkish tweet ids one month before and after of pandemic outbreak. You can see the tweets classified across COVID, economy, politics, religion, disinformation, international relations themes. To see research design and analyze the code for the text analysis please visit this link: <a href="https://github.com/burakozturan/tria-covid19">https://github.com/burakozturan/css_covid19</a></p>
Data from: Effects of taxon sampling and tree reconstruction methods on phylodiversity metrics
1. The amount and patterns of phylodiversity in a community are often used to draw inferences about the local and historical factors affecting community assembly and can be used to prioritize communities and locations for conservation. Because measures of phylodiversity are based on the topology and branch lengths of phylogenetic trees, which are affected by the number and diversity of taxa in the tree, these analyses may be sensitive to changes in taxon sampling and tree reconstruction methods. 2. To investigate the effects of taxon sampling and tree reconstruction methods on measures of phylodiversity, we investigated the community phylogenetics of the Ordway-Swisher Biological Station (Florida), which is home to over 600 species of vascular plants. We studied the effects of 1) the number of taxa included in the regional phylogeny; 2) random vs. targeted sampling of species to assemble the regional species pool; 3) including only species from specific clades rather than broad sampling; 4) using trees reconstructed directly for the taxa under study compared to trees pruned from a larger reconstructed tree; and 5) using phylograms compared to chronograms. 3. We found that including more taxa in a study increases the likelihood of observing significantly non-random phylogenetic patterns. However, there were no consistent trends in the phylodiversity patterns based on random taxon sampling compared to targeted sampling, or within individual clades compared to the complete dataset. Using pruned and reconstructed phylogenies resulted in similar patterns of phylodiversity, while chronograms in some cases led to significantly different results from phylograms. 4. The methods commonly used in community phylogenetic studies can significantly impact the results, potentially influencing both inferences of community assembly and conservation decisions. We highlight the need for both careful selection of methods in community phylogenetic studies and appropriate interpretation of results, depending on the specific questions to be addressed.
Glassware images and code samples for training and identification of glassware by neural networks
<p>These images were used to perform an image identification exercise with first-year students in the author's Introduction to Scientific Computing course. The zip file also includes sample Mathematica notebooks that were used to perform the training and data analysis of the neural network's performance. The corresponding publication in the Journal of Computational Science Education can be found here <a href="https://doi.org/10.22369/issn.2153-4136/12/1/2">https://doi.org/10.22369/issn.2153-4136/12/1/2</a></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.