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2,863
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Dataset results
2,863 results for “Challenge”
Massively Parallel Binding Assay (MPBA) reveals limited transcription factor cooperation, challenging models of specificity
GEO Series GSE234455. Saccharomyces cerevisiae. 40 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing.
Transcriptomic signature of in vitro heat stress challenged porcine granulosa cells
GEO Series GSE243234. Sus scrofa. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell RNA sequencing of the liver cells from 2-month-old A/A and S/S mice with or without TNF challenge.
GEO Series GSE250171. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
The sea urchin larval response to immune challenge with Vibrio diazotrophicus
GEO Series GSE96940. Strongylocentrotus purpuratus. 4 samples. Type: Expression profiling by high throughput sequencing.
Gene expression and cytokine profile correlate with mycobacterial growth in a human BCG challenge model
GEO Series GSE58636. Homo sapiens. 177 samples. Type: Expression profiling by array.
Facing warm temperatures during migration – cardiac mRNA responses of two adult sockeye salmon Oncorhynchus nerka populations to warming and swimming challenges
GEO Series GSE50054. Oncorhynchus mykiss; Oncorhynchus nerka; Salmo salar. 8 samples. Type: Expression profiling by array.
Mouse liver: Control versus IL1-beta challenge, male and female
GEO Series GSE54071. Mus musculus. 8 samples. Type: Expression profiling by array.
m6A RNA methylation mediates NOD1/NF-kB signaling activation in the liver of piglets challenged with lipopolysaccharide
GEO Series GSE209858. Sus scrofa. 15 samples. Type: Methylation profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Transcriptome analysis of Cox4-2 knockout mice after OVA challenge
GEO Series GSE49694. Mus musculus. 16 samples. Type: Expression profiling by array.
Therapeutic intervention of monocytes to LPS challenge
GEO Series GSE65855. Homo sapiens. 21 samples. Type: Expression profiling by array.
Metabolic flexibility of a prospective bioremediator: Desulfitobacterium hafniense Y51 challenged in chemostats
GEO Series GSE107146. Desulfitobacterium hafniense; Desulfitobacterium hafniense Y51. 10 samples. Type: Expression profiling by array.
Transcriptional response of turkey blood leukocytes challenged with Salmonella enterica serovar Typhimurium UK1
GEO Series GSE151896. Meleagris gallopavo. 7 samples. Type: Expression profiling by high throughput sequencing.
A SWEET Challenge: Less Sugar for Rhizospheric Microbiome Under the Successive Wheat Cultivatoin
GEO Series GSE299883. Triticum aestivum. 12 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome profiles in the spleen of the Chinese giant salamander (Andrias davidianus) challenged with Citrobacter freundii
GEO Series GSE137296. Andrias davidianus. 6 samples. Type: Expression profiling by high throughput sequencing.
Next-generation sequencing analysis of vehicle and rmMETRNL mouse macrophages challenged with Candida albicans.
GEO Series GSE290122. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis reveals differential response in the teleost spleens and head kidneys towards vaccination and pathogen challenge
GEO Series GSE51839. Lates calcarifer. 57 samples. Type: Expression profiling by array.
Response of Bacillus cereus ATCC 14579 to challenges with sublethal concentrations of enterocin AS-48
GEO Series GSE15600. Bacillus cereus ATCC 14579. 6 samples. Type: Expression profiling by array.
Expression analysis of channel catfish anterior kidney at 48h post immersion challenge of vaccinated fish (28 days post vaccination with attenuated Edwardsiella ictaluri) with virulent E. ictaluri
GEO Series GSE32588. Ictalurus punctatus. 6 samples. Type: Expression profiling by array.
Transcriptome analysis of the kidney of obscure puffer Takifugu obscurus challenged with poly(I:C)
GEO Series GSE181941. Takifugu obscurus. 9 samples. Type: Expression profiling by high throughput sequencing.
Data Corpus for the IEEE-AASP Challenge on Acoustic Source Localization and Tracking (LOCATA)
<p>This repository contains the final release of the development and evaluation datasets for the LOCATA Challenge.</p> <p>The challenge of sound source localization in realistic environments has attracted widespread attention in the Audio and Acoustic Signal Processing (AASP) community in recent years. Source localization approaches in the literature address the estimation of positional information about acoustic sources using a pair of microphones, microphone arrays, or networks with distributed acoustic sensors. The IEEE AASP Challenge on <strong>acoustic source LOCalization And TrAcking (LOCATA)</strong> aimed at providing researchers in source localization and tracking with a framework to objectively benchmark results against competing algorithms using a common, publicly released data corpus that encompasses a range of realistic scenarios in an enclosed acoustic environment.</p> <p>Four different microphone arrays were used for the recordings, namely:</p> <ul> <li>Planar array with 15 channels (DICIT array) containing uniform linear sub-arrays</li> <li>Spherical array with 32 channels (Eigenmike)</li> <li>Pseudo-spherical array with 12-channels (robot head)</li> <li>Hearing aid dummies on a dummy head (2-channel per hearing aid).</li> </ul> <p>An optical tracking system (OptiTrack) was used to record the positions and orientations of talker, loudspeakers and microphone arrays. Moreover, the emitted source signals were recorded to determine voice activity periods in the recorded signals for each source separately. The ground truth values are compared to the estimated values submitted by the participants using several criteria to evaluate the accuracy of the estimated directions of arrival and track-to-source association. </p> <p>The datasets encompass the following six, increasingly challenging, scenarios:</p> <ul> <li><strong>Task 1:</strong> Localization of a single, static loudspeaker using static microphones arrays</li> <li><strong>Task 2:</strong> Multi-source localization of static loudspeakers using static microphone arrays</li> <li><strong>Task 3:</strong> Localization of a single, moving talker using static microphone arrays</li> <li><strong>Task 4:</strong> Localization of multiple, moving talkers using static microphone arrays</li> <li><strong>Task 5:</strong> Localization of a single, moving talker using moving microphone arrays</li> <li><strong>Task 6:</strong> Multi-source localization of moving talkers using moving microphone arrays.</li> </ul> <p>The development and evaluation datasets in this repository contain the following data:</p> <ul> <li>Close-talking speech signals for human talkers, recorded use DPA microphones</li> <li>Distant-talking recordings using four microphone arrays: <ul> <li>Spherical Eigenmike (32 channels)</li> <li>Pseudo-spherical prototype NAO robot (12 channels)</li> <li>Planar DICIT array (15 channels)</li> <li>Hearing aids installed in a head-torso simulator (4 channels)</li> </ul> </li> <li>Ground-truth annotations of all source and microphone positions, obtained using an OptiTrack system of infrared cameras. The ground-truth positions are provided at the frame rate of the optical tracking system</li> </ul> <p>The following software is provided with the data:</p> <ul> <li>Matlab code to read the datasets: <a href="https://github.com/cevers/sap_locata_io">github.com/cevers/sap_locata_io</a></li> <li>Matlab code for performance evaluation of localization and tracking algorithms: <a href="https://github.com/cevers/sap_locata_eval">github.com/cevers/sap_locata_eval</a></li> </ul> <p>For further information, see:</p> <ul> <li>C. Evers, H. W. Löllmann, H. Mellmann, A. Schmidt, H. Barfuss, P. A. Naylor, W. Kellermann<br> <em>"</em>The LOCATA Challenge: Acoustic Source Localization and Tracking<em>," </em>in <em>IEEE/ACM Transactions on Audio, Speech, and Language Processing</em>, vol. 28, pp. 1620-1643, 2020, doi: <a href="https://doi.org/10.1109/TASLP.2020.2990485">10.1109/TASLP.2020.2990485</a></li> <li>Documentation: <a href="https://www.locata.lms.tf.fau.de/files/2020/01/Documentation_LOCATA_final_release_V1.pdf">https://www.locata.lms.tf.fau.de/files/2020/01/Documentation_LOCATA_final_release_V1.pdf</a></li> </ul>
ScienceDex guides
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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.