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3,081 results for “arrays”
Unraveling the Sox4-orchestrated pro-B cell differentiation program: Intricate roles of the RAG and CK1ε genes (RNA array)
GEO Series GSE50065. Mus musculus. 12 samples. Type: Expression profiling by array.
Genomic aberrations in distant fields from oral potentially malignant lesions by high resolution DNA flow cytometry and array-CGH
GEO Series GSE28906. Homo sapiens. 32 samples. Type: Genome variation profiling by genome tiling array.
ETV1 and ERG genome binding/occupancy profiling by genome tiling array
GEO Series GSE39357. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by genome tiling array.
Genomic profiling of IPMN with an associated invasive carcinomas (IPMN-inv) and invasive ductal carcinomas (IDC) by array-based comparative genomic hybridization
GEO Series GSE65181. Homo sapiens. 39 samples. Type: Genome variation profiling by array.
Gene expression profiling of Drosophila melangoaster Myb mutant wing discs of 3rd instar larvae. [NimbleGen tiling array]
GEO Series GSE100141. Drosophila melanogaster. 8 samples. Type: Expression profiling by genome tiling array.
Comprehensive circRNAs expression profiling reveals the potential role of circRNAs in systemic lupus erythematosus [Human circRNA Array v2.0]
GEO Series GSE84655. Homo sapiens. 9 samples. Type: Non-coding RNA profiling by array.
High-resolution map of copy number variations in motor cortex of Control and Sporadic Amyotrphic Lateral Sclerosis patients by using a customized exon-centric comparative genomic hybridization array.
GEO Series GSE107375. Homo sapiens. 40 samples. Type: Genome variation profiling by array.
CRISPR/dCas9 DNA methylation editing is heritable during human haematopoiesis and can impair differentiation in vivo [methylation array]
GEO Series GSE222178. Homo sapiens. 9 samples. Type: Methylation profiling by genome tiling array.
Array CGH of Drosophila ChrX deficiencies_duplications on heterochromatin custom array.
GEO Series GSE36262. Drosophila melanogaster. 8 samples. Type: Genome variation profiling by array.
Detection of S. cerevisiae fragments in the genome of S. bayanus strains with aCGH on Yeast_2 Affymetrix array.
GEO Series GSE28225. Schizosaccharomyces pombe; Saccharomyces bayanus; Saccharomyces uvarum; Saccharomyces cerevisiae. 5 samples. Type: Genome variation profiling by array.
llumina 450k array was used to identify DNA methylation data from formalin-fixed paraffine-embedded (FFPE) human uveal melanoma correlated to gene expression, metastasis and poor prognosis
GEO Series GSE156876. Homo sapiens. 23 samples. Type: Methylation profiling by array.
Porous carbon nanowire array for surface-enhanced Raman spectroscopy
<p>Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for vibrational spectroscopy as it provides several orders of magnitude higher sensitivity than inherently weak spontaneous Raman scattering by exciting localized surface plasmon resonance (LSPR) on metal substrates. However, SERS can be unreliable for biomedical use since it sacrifices reproducibility, uniformity, biocompatibility, and durability due to its strong dependence on “hot spots”, large photothermal heat generation, and easy oxidization. Here we demonstrate the design, fabrication, and use of a metal-free (i.e., LSPR-free), topologically tailored nanostructure composed of porous carbon nanowires in an array as a SERS substrate to overcome all these problems. Specifically, it offers not only high signal enhancement (~10<sup>6</sup>) due to its strong broadband charge-transfer resonance, but also extraordinarily high reproducibility due to the absence of hot spots, high durability due to no oxidization, and high compatibility to biomolecules due to its fluorescence quenching capability.</p>
Figures and graphics used in "Optimizing Strength of Shared Anchors in an Array of Floating Offshore Wind Turbines"
<p>All figures and graphics used in tables are included in PDF format here. Instructions on how to reproduce the MATLAB-generated plots (or similar plots) are included in the README of the software package, also cited in the paper.</p>
Source Data of "Coherent control of individual electron spins in a 2D quantum dot array"
<p>Coherent manipulation of individual quantum objects organized in arrays is a prerequisite to any scalable quantum information platform.<br> The cumulated efforts to control electron spins in quantum dot arrays have permitted the recent realization of quantum simulators and multi-electron spin coherent manipulations.<br> While being a natural path to resolve complex quantum matter problems and to process quantum information, the two-dimensional (2D) scaling with high connectivity of such implementations remains undemonstrated.<br> Here, we demonstrate the 2D coherent control of individual electron spins in a 3x3 array of tunnel coupled quantum dots.<br> We focus on several key quantum functionalities: charge deterministic loading and displacement, local spin readout, and local coherent exchange manipulation between two electron spins trapped in adjacent dots.<br> This work lays some of the foundations for exploiting a 2D array of electron spins for quantum simulation and information processing.</p>
Allen Telescope Array Galileo E31 RF recording with 2 antennas and 2 polarizations
<p>This is a short recording of Galileo satellite GSAT0218 (E31) done with two antennas at Allen Telescope Array in the E1 (1575.42 MHz) frequency band, using a sample rate of 30.72 Msps.</p> <p>The recording was done with antennas 1h and 4g, and both polarizations X and Y from each antenna. The recording lasts approximately 15 seconds and was done on 2020-10-04.</p> <p>The hardware configuration was as follows: antennas 1h and 4g were connected to RFCB LO d, which was tuned to a frequency of 1475.42 MHz and used an output IF of 629 MHz. Two USRPs N32x were connected to the IF output of the RFCB. The first USRP digitized signals from both polarizations of antenna 1h, while the second USRP digitized signals from both polarizations of antenna 4g. The USRPs used external 10 MHz reference and PPS coming from the observatory distribution system.</p> <p>This dataset contains the baseband IQ recordings for each antenna and polarization in <a href="https://github.com/gnuradio/SigMF">SigMF</a> format.</p> <p>More information about the dataset can be found in the blog post "<a href="https://destevez.net/2020/10/gnss-interferometry-at-allen-telescope-array/">GNSS Interferometry at Allen Telescope Array</a>" by the first author.</p> <p><strong>Note:</strong> during the recording there was a problem with caused phase-modulation of the signals at 60 Hz and harmonics. The phase-modulation effect is common to all the channels, so interferometry applications of this data are not affected by it. However, this problem makes it somewhat difficult to perform tracking of the GNSS signals in the usual manner.</p>
Allen Telescope Array polarimetric observation of GNSS satellites
<p>This dataset contains polarimetric observations of several GNSS satellites done with two antennas at Allen Telescope Array in the E1 (1575.42 MHz) frequency band. The dataset consists of power spectra and cross-spectra for the X and Y linear polarizations of each antenna. A total of 1024 FFT channels are used with an input sample rate of 24.576Msps (IQ sampling) to give a frequency resolution of 24kHz. The |X|^2, |Y|^2 and X*conjugate(Y) cross-spectra are coherently averaged in windows of 0.1 seconds.</p> <p><strong>Note:</strong> only one out of every four 1024 IQ sample vectors was processed in order to reduce the CPU load during data recording, so the effective averaging of each spectrum is only 25ms.</p> <p>The recording was done with antennas 1h and 4g on 2020-10-24, and it includes several minutes of measurements for the Galileo satellites E01, E13, E26, E31, E33, and the GPS satellite G05.</p> <p>The hardware configuration was as follows: the antennas were connected to RFCB LO d, which was tuned to a frequency of 1475.42 MHz and used an output IF of 512 MHz. A USRPs N321 and a USRP N320 were connected to the IF output of the RFCB. Each of the USRPs was used to digitized both polarizations from one of the antenna. The USRPs used external 10 MHz reference and PPS coming from the observatory distribution system. LO sharing was configured between all of the USRPs channels.</p> <p>The dataset contains a flat .tar.xz archive with several files having names such as E01_2020-10-24T11:37:38.353705_0xx. The beginning of the filename indicates the target of the observation, then there is the UTC timestamp corresponding to the beginning of the observation, and finally a code that indicates the measurement channel. The first character of the code is either 0 or 1 to indicate antenna 1h or antenna 4g respectively. The remaining characters can be either xx or yy for the power spectra of polarizations X and Y respectively or xy for the cross-spectra of polarizations X and Y.</p> <p>The timestamp for the data is only approximate, because it refers to the instant at which the data collection script started. The USRPs take some 10 to 30 seconds to initialize after this.</p> <p>The format for the xx and yy power spectra files is raw binary in IEEE 754 32 bit floats, with every 1024 elements of the file constituting a power spectra. The format for the xy cross spectra files is raw binary in IEEE 754 32 bit floats. Each pair of floats represents the real and imaginary parts of a complex number. Every 1024 pairs of floats constitute a cross-spectra. Consecutive spectra are separated 0.1 seconds apart in both cases.</p> <p>More information about the dataset can be found in the blog post "<a href="https://destevez.net/2020/10/ata-polarimetry-test-with-gnss-satellites/">ATA polarimetry test with GNSS satellites</a>" by the first author.</p>
Allen Telescope Array polarimetric observation of 3C286
<p>This dataset contains a polarimetric interferometry observation of the quasar 3C286 done with two dishes from Allen Telescope Array on 2020-10-31. The observation was done during two hours around transit, so it has large parallactic angle coverage. Eight different frequency bands between 1 and 8 GHz were observed in turns. Scans of 100 seconds were done with a frequency change between each scan.</p> <p>The frequency bands observed are 1413 MHz, 1665 MHz, 2675 MHz, 4820 MHz, 6663 MHz, and 8665 MHz. A total of 30.72 MHz of spectrum divided in 256 frequency bins were observed in each band. This data set contains the same data in two formats: the raw measurements produced with GNU Radio, and the observations in UVFITS format.</p> <p>The raw measurements consists of power spectra and cross-spectra for the X and Y linear polarizations of each antenna, using a coherent averaging interval of 0.1 seconds.</p> <p>The observation was done with antennas 1h and 4g from the array, using two USRP N32x to digitize the signals, and GNU Radio to perform the digital signal processing. Both of the antennas were connected to LO d in the RF converter board, which downconverted the signals to a 512 MHz IF. The two channels of each USRP were used to digitize the two polarization channels of each antenna. The USRPs were configured to share the LO between all the channels, and were synchronized to the 10 MHz and 1PPS signals from the telescope timing distribution system.</p> <p>The raw measurements are not phased to the source: instrumental and geometric delays are not corrected in any way.</p> <p>All the raw measurements are stored in GNU Radio Metdata files with detached headers, contained in a flat .tar.xz archive. These files have names such as 3c286_2020-10-31T17:47:32.114581_cross_0. The beginning of the filename indicates the target of the observation, then there is the UTC timestamp corresponding to the beginning of the observation, and finally a code that indicates the measurement channel.</p> <p>Measurement channels are divided in "power" for (real-valued) PSD and "cross" for (complex-valued) cross spectra. The "power" channels are numbered 0 through 3 and correspond to |X1|^2, |Y1|^2, |X2|^2 and |Y2|^2, where Xj and Yj denote the X and Y polarizations of antenna j (here j = 1 corresponds to antenna 1h and j = 2 corresponds to antenna 4g). The "cross" channels are numbered 0 through 5 and correspond to <X1,Y1>, <X1,X2>, <X1,Y2>, <Y1,X2>, <Y1,Y2>, <X2,Y2>.</p> <p>Each file corresponds to one channel and one scan. The metadata detached header contains useful information, such as the precise timestamping of the samples and the observation frequency. Note that some of the files have invalid timestamps in the metadata (they are easy to distinguish because their first timestamp is zero). The timestamp in the filename is only a coarse estimate, and is typically within 1 second error of the precise timestamp in the metadata.</p> <p>The UVFITS files contain only the cross-spectra between different antennas (correlations XX, YY, XY and YX). The data is phased to the source, but the same number of frequency channels and integration interval is maintained. There is one UVFITS file per frequency band.</p> <p>More information about this observation and dataset can be found in the post "<a href="https://destevez.net/2020/11/polarimetric-observation-of-3c286-with-allen-telescope-array/">Polarimetric observation of 3C286 with Allen Telescope Array</a>" by the first author.</p>
Chang'e 5 RF recording at 8463.7 MHz with Allen Telescope Array during LOI-2
<p>This dataset contains a recording of X-band telemetry signals from the Chinese lunar sample retrieve mission Chang'e 5 done on 2020-11-29 before and during the LOI-2 (lunar orbit injection 2) manoeuvre that circularized the spacecraft's elliptical lunar orbit. The recording was done at Allen Telescope Array using antenna 1h in dual XY (linear) polarization.</p> <p>The hardware configuration was as follows: antennas 1h was connected to RFCB LO d, which was tuned to a frequency of 8475 MHz and used an output IF of 512 MHz. A USRP N321 was connected to the IF output of the RFCB and digitized both polarizations. The USRP used external 10 MHz reference and PPS coming from the observatory distribution system. The IQ sample rate of the USRP was 30.72 Msps and a GNU Radio flowgraph was used to channelize four frequencies from the spacecraft (8463.7, 8471.2, 8478.6 and 8486.2 MHz), using an IQ sample rate of 240 ksps for each channel.</p> <p>The GNU Radio flowgraph stored the IQ data for each channel as 32-bit floats in the <a href="https://wiki.gnuradio.org/index.php/Metadata_Information">GNU Radio metatata file format</a>, with detached headers. After recording, the data was converted to <a href="https://github.com/gnuradio/SigMF">SigMF</a> format.</p> <p>This dataset contains the IQ data for the channel at 8463.7 MHz, which corresponds to the lander, in SigMF format. Each polarization is in a different file. The original metadata headers are also provided.</p> <p><strong>Note:</strong> during the observation, the frequency of the RFCB LO was lowered by exactly 30 kHz in two occasions to prevent the signals from drifting out of the channel passband due to Doppler. The two LO jumps can be easily seen in the residual carrier of the signals and corrected.</p>
Data from: Adjustable temperature array for characterising ecological and evolutionary effects on thermal physiology
1. To accurately characterise a species' thermal niche and aid in predicting effects of climate change we must not only include information on thermal tolerances and physiological responses to changing temperatures, but also incorporate ecological effects and evolutionary processes that may shape a species' niche. However, quickly and practically collecting data on key factors such as adaptation potential, behaviour, effects of species interactions, plasticity, and thermal tolerances is logistically challenging. 2. We have therefore created an adjustable temperature array (ATA) to assist with experimental ecology and evolution research. ATA's are a row of independent temperature points controlled and set by the user and made from commercially-available parts. This allows the user to create unique thermal landscapes relevant to their study organism(s) and question(s). Further, the option of using an enclosed cage allows the user to answer questions at the individual, population, or community level in the context of changing thermal environments. ATA's are able to be user-set to constant or dynamic temperature regimes and are designed for use on small animals (e.g., fruit flies, beetles, mosquitoes) or plants (e.g., germinating seeds). 3. We have tested and confirmed the accuracy of the ATA to several thermal landscapes that would be useful for experimental ecology and evolution, including: 1) coarse resolution of a broad thermal niche ranging from 12° to 42°C in 2°C intervals (R2= 0.998); 2) fine resolution of a narrow thermal niche ranging from 15° to 32°C in 1°C intervals (R2= 0.997); 3) a pyramid-shaped niche consisting of a gradient from 14° to 30°C in 2°C intervals (R2 = 0.997); and 4) a very narrow thermal niche with replicate thermal resources ranging from 26.5° to 34°C in 1.5°C. intervals (R2= 0.989). 4. The equipment described here is an important tool for thermal niche studies and will aid in gathering information on effects of ecological and evolutionary processes to create a comprehensive picture of species responses to climate change.
MeerTime Thousand Pulsar Array Data Release
<p>Data associated with the MeerTime Thousand Pulsar Array Data Release. Please cite Keith et al., MNRAS, (2024), <em>"The Thousand-Pulsar-Array programme on MeerKAT XIII: Timing, flux density, rotation measure and dispersion measure timeseries of 597 pulsars"</em> and refer to this paper for important details on this dataset.</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.