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286 results for “mocking”
Data from: ITS all right mama: Investigating the formation of chimeric sequences in the ITS2 region by DNA metabarcoding analyses of fungal mock communities of different complexities
The formation of chimeric sequences can create significant methodological bias in PCR-based DNA metabarcoding analyses. During mixed-template amplification of barcoding regions, chimera formation is frequent and well documented. However, profiling of fungal communities typically uses the more variable rDNA region ITS. Due to a larger research community, tools for chimera detection have been developed mainly for the 16S/18S markers. However, these tools are widely applied to the ITS region without verification of their performance. We examined the rate of chimera formation during amplification and 454 sequencing of the ITS2 region from fungal mock communities of different complexities. We evaluated the chimera detecting ability of two common chimera-checking algorithms: Perseus and UCHIME. Large proportions of the chimeras reported were false positives. No false negatives were found in the dataset. Verified chimeras accounted for only 0.2% of the total ITS2 reads, which is considerably less than what is typically reported in 16S and 18S metabarcoding analyses. Verified chimeric "parent sequences" had significantly higher percent identity to one another than to random members of the mock communities. Community complexity increased the rate of chimera formation. GC content was higher around the verified chimeric break points, potentially facilitating chimera formation through base pair mismatching in the neighboring regions of high similarity in the chimeric region. We conclude that the hypervariable nature of the ITS region seem to buffer the rate of chimera formation in comparison to other, less variable barcoding regions, due to shorter regions of high sequence similarity.
The mock samples for high-z spectroscopic galaxy survey
<p>The mock samples for high-z spectroscopic galaxy survey. The dataset includes zCOSMOS, VIPERS and PFS-like galaxy survey's mock samples. The final design of PFS galaxy survey is not determined. So if you want to get the PFS-like mocks, please contact meng.jiacheng@foxmail.com or go to https://lig.astro.tsinghua.edu.cn/astrodata.</p> <p>The files named as "lu14_zcosmos_mock_index.h5df" are mocks for zCOSMOS survey. The files named as "lu14_w1_mock_index.h5df" and "lu14_w4_mock_index.h5df" are mocks for VIPERS survey, where "w1" and "w4" represent the two fields of VIPERS survey. Index is from 0 to19, representing the 20 mocks with different direction of line-of-sight when constructing mocks. The meanings of the keys in hdf5 files are as follows:</p> <ul> <li>"ra" and "dec": coordiantes;</li> <li>"z_spec" and "z_phot": spectroscopic redshift and photometric redshift;</li> <li>"stellar_mass": stellar mass;</li> <li>"sfr": star formation rate;</li> <li>"halo_mass": halo mass;</li> <li>"group_index": ID of the galaxy group for the given galaxy;</li> <li>"central_flag": 1 for central galaxy, 0 for satellite galaxy;</li> <li>"m_*": apparent magnitude;</li> <li>"M_*": absolute magnitude;</li> <li>"flag": 0 for no observation, 1 for galaxy having spectroscopic redshift, others for galaxy only having photometric redshift;</li> <li>"snap": the snapshot of the model galaxy;</li> <li>"model_index": the ID of the model galaxy;</li> <li>"box_index": the box ID where the model galaxy are in when constructing mocks.</li> </ul>
mock interview with caretaker for ABA based pediatric feeding therapy
<p>cover all the basis: variety, volume, reinforcers, termination of meals, meal location, feeder, self or nonself feeder, texture, medical background... </p>
mock parental/ caregiver interview for pediatric feeding intake
<p>This is a mock interview. It covers most of the basics. Good to conduct this type of interview prior to home baseline and assessment. </p>
Mock up dataset for daGOAT project
<p>This dataset, which contains mocked severe-aGVHD data, is intended to be used as test input for ./Code/severe-aGVHD/ in daGOAT project (https://github.com/chenjunren-ihcams/daGOAT). </p> <p> </p> <p>The dataset include three parts.</p> <p>1) all dynamic features for each patient across the whole observation time is provided as single csv file under /processed folder</p> <p>2) all peri-transplantation features, presence/absence of severe aGVHD within 100 days, and onset dates of severe aGVHD are provided in "encoded.csv"</p> <p>3) The name of each dynamic folder is provided in "keys.csv"</p>
Hemodynamic data from the Inspired Therapeutics NeoMate Mechanical Circulatory Support System for neonates and infants as tested in static mock circulatory loops, dynamic mock circulatory loops, and acute animal studies
<p>Inspired Therapeutics (Merritt Island, FL) is developing a mechanical circulatory support (MCS) system designed as a single driver with interchangeable, extracorporeal, magnetically levitated pumps. The NeoMate system design features an integrated centrifugal rotary pump, motor, and controller that will be housed in a single compact unit. Conceptually, the primary innovation of this technology will be the combination of disposable, low-cost pumps for use with a single, multi-functional, universal controller to support multiple pediatric cardiopulmonary indications. In response to the paucity of clinically available pediatric devices, Inspired Therapeutics is specifically targeting the underserved neonate and infant heart failure (HF) patient population first. In this article, we present the development of the prototype Inspired Therapeutics NeoMate System for pediatric left ventricular assist device (LVAD) support, and feasibility testing in static mock flow loops (H-Q curves), dynamic mock flow loops (hemodynamics), and in an acute healthy ovine model (hemodynamics and clinical applicability). The resultant hydrodynamic and hemodynamic data demonstrated the ability of this prototype pediatric LVAD and universal controller to function over a range of rotary pump speeds (500-6000 RPM), to provide pump flow rates of up to 2.6 L/min, and to volume unload the left ventricle in acute animals. Key engineering challenges observed and proposed solutions for the next design iteration are also presented.</p>
In silico mock communities for evaluation of taxonomic profilers across eukaryotes in the human microbiome
<p><em>In silico </em>mock communities generated with CAMISIM for benchmarking the performance of taxonomic profilers across prokaryotic (50 communities), eukaryotic (30 communities), and viral communities (10 communities) of the human microbiome. Metagenomes were generated using CAMISIM (Fritz et al., 2019), which simulates 2.1 Gb of Illumina 2 ×150 bp paired end reads with the default HiSeq 2500 error profile and a mean insert size of 200 bp.</p> <p><strong>Eukaryotic communities<br></strong>30 eukaryotic <em>in silico</em> metagenomes comprising up to 200 randomly sampled genomes from a set of 113 eukaryotic species (See Supplementary Table 2 from the paper) corresponding to the eukaryotic species within both CHAMP and MetaPhlAn 4 (Blanco-Míguez et al., 2023) databasess.</p> <p><strong>Prokaryotic and viral communities</strong></p> <p>In silico data for prokaryotic and viral communities from the human microbiome can be found here: <a href="https://doi.org/10.5281/zenodo.10777404">doi: 10.5281/zenodo.10777404</a></p> <p><strong>References</strong></p> <p>Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., et al. (2023). Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. <em>Nature Biotechnology 2023 41:11</em> 41, 1633–1644. doi: 10.1038/s41587-023-01688-w</p> <p>Fritz, A., Hofmann, P., Majda, S., Dahms, E., Dröge, J., Fiedler, J., et al. (2019). CAMISIM: Simulating metagenomes and microbial communities. <em>Microbiome</em> 7, 1–12. doi: 10.1186/S40168-019-0633-6/FIGURES/5</p>
Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey
<p>Supplementary material to DESI's publication "Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey" to comply with the data management plan. This includes the Python scripts and data points required to reproduce all figures in the publication.</p>
Mock community REMEI
<p>Mock community sequenced with Illumina for quality control purposes. </p>
Impurity gas detection dataset on 2/3-scaled canister mock-up
<p>This repository contains datasets used for training Variational Autoencoders (VAE) and Wasserstein Autoencoders (WAE) in the detection of impurity gases on a 2/3-scaled sealed canister mock-up. The research focuses on identifying abnormal gas concentrations using acoustic sensing techniques. These datasets were utilized in the study titled "Acoustic Sensing and Auto-encoder Approach for Abnormal Gas Detection on a Spent Nuclear Fuel Canister Mock-up."</p> <p>Files</p> <p>1. X_train_helium(argon).npy: This file contains the training data with helium in day-1.<br>2. Argon_Percentage.npy: This file contains the different impurity levels of argon used in the experiments.<br>3. impurity_data.npz: This file is a dictionary containing ultrasonic response data for various argon impurity levels.<br>4. X_train_helium(air).npy: This file contains the training data with helium in day-2.<br>5. Air_Percentage.npy: This file contains the different impurity levels of argon used in the experiments.<br>6. impurity_data.npz: This file is a dictionary containing ultrasonic response data for various air impurity levels.</p> <p><br>Data Structure</p> <p>X_train_helium(argon).npy<br>- Shape: (1,991, 301)<br>- Description: This array contains the training data, where:<br> - Each of the 1,991 rows represents a unique sample.<br> - The 301 columns represent the truncated ultrasonic response for each sample.</p> <p>X_train_helium(air).npy<br>- Shape: (988, 301)<br>- Description: This array contains the training data, where:<br> - Each of the 988 rows represents a unique sample.<br> - The 301 columns represent the truncated ultrasonic response for each sample.</p> <p>Argon_Percentage.npy or Air_Percentage.npy<br>- Shape: (41, 1)<br>- Description: This array contains the impurity levels of argon and air used in the experiments. There are 41 different impurity levels, each represented by a percentage in this file.</p> <p>impurity_data.npz<br>- Structure: This file is a dictionary containing 40 items, each representing data for a specific argon impurity concentration level.<br>- Description: Each item in the dictionary is structured as follows:<br> - Shape: (51, 301)<br> - Details:<br> - The 51 rows represent repeated ultrasonic response measurements at each impurity concentration level.<br> - The 301 columns represent the truncated ultrasonic response corresponding to each measurement.</p> <p>Contact<br>For any questions or issues related to this dataset, please contact the repository owner via bozhouzh@usc.edu.</p>
2 pt statistics of mocks halo/galaxy catalogs
<p>Summary of two point statistics of the halo/galaxy catalogs in Fourier space.</p>
mock-up for geometry change analysis
<p>The ceramic object belongs to the Ceramic Conservation and Restoration Studio at the Faculty of Conservation and Restoration of Works of Art, Academy of Fine Arts in Warsaw, Poland. This is a mockup tile prepared for the geometry change assessment. The dataset has been presented in the article "Segmentation of Change in Surface Geometry Analysis for Cultural Heritage Applications" (https://www.mdpi.com/1424-8220/21/14/4899).</p>
Mapped ATAC-seq data for mock and HSV-1 strain 17 infection and infection with null mutants of HSV-1
<p>Sample annotation:</p> <table> <tbody> <tr> <td>Mock_1</td> <td>mock infection, replicate 1</td> </tr> <tr> <td>Mock_2</td> <td>mock infection, replicate 2</td> </tr> <tr> <td>WT_1</td> <td>HSV-1 wt, strain 17, replicate 1</td> </tr> <tr> <td>WT_2</td> <td>HSV-1 wt, strain 17, replicate 2</td> </tr> <tr> <td>WT_plus_PAA_1</td> <td>HSV-1 wt, strain 17, +PAA, replicate 1</td> </tr> <tr> <td>WT_plus_PAA_2</td> <td>HSV-1 wt, strain 17, +PAA, replicate 2</td> </tr> <tr> <td>dICP0_1</td> <td>HSV-1 lacking expression of ICP0, replicate 1</td> </tr> <tr> <td>dICP0_2</td> <td>HSV-1 lacking expression of ICP0, replicate 2</td> </tr> <tr> <td>dICP22_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 1</td> </tr> <tr> <td>dICP22_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 2</td> </tr> <tr> <td>dICP22_3</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 3</td> </tr> <tr> <td>dICP22_4</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 4</td> </tr> <tr> <td>dICP22_plus_PAA_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 1</td> </tr> <tr> <td>dICP22_plus_PAA_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 2</td> </tr> <tr> <td>dICP27_1</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 1</td> </tr> <tr> <td>dICP27_2</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 2</td> </tr> <tr> <td>dVHS_1</td> <td>HSV-1 lacking expression of UL41, replicate 1</td> </tr> <tr> <td>dVHS_2</td> <td>HSV-1 lacking expression of UL41, replicate 2</td> </tr> </tbody> </table>
Supplementary material 9 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Processed TaXon tables of each primer pair (subtracted negative controls and filtered for fish and lamprey taxa OTUs)
Supplementary material 1 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Pairwise comparison of the log-transformed reads of the non-normalized mock community (MC1) compared to the DNA concentration (ng/ul) of each species
Supplementary material 3 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Sampled specimens and their respective species assignment collected for the fish mock community, extraction date, collection site, and concentration after DNA extraction
Supplementary material 4 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
List of all species reported from Germany, their occurrence status, and their presence in the mock community (data from fishbase.org)
Supplementary material 2 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Pairwise comparison of the log-transformed reads of the non-normalized mock community (MC1) compared to log-transformed reads of the normalized mock community (MC2) of each species
CEH_mock_bamfiles
<p>Bam files from two samples run with MetaScope!</p>
Impact of a Mock-up Fact-checking Extension on HPV Vaccine Misinformation: A Survey Experiment
ClinicalTrials.gov study NCT06405048. IPD Sharing: YES. Countries: 1. Publications: 17.
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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.