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212 results for “Data Drift”

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dryad28/100

Data from: Sex chromosome turnovers and genetic drift: a simulation study

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publicJun 2018View details →
dryad28/100

Data from: Establishment and maintenance of adaptive genetic divergence under migration, selection, and drift

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publicFeb 2011View details →
dryad28/100

Data from: The action of stabilizing selection, mutation and drift on epistatic quantitative traits

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publicMar 2014View details →
dryad28/100

Data from: Disentangling the roles of natural selection and genetic drift in shaping variation at MHC immunity genes

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publicAug 2011View details →
dryad28/100

Data from: Genetic drift and rapid evolution of viviparity in insular fire salamanders (Salamandra salamandra)

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publicSep 2011View details →
dryad28/100

Data from: Sampling schemes and drift can bias admixture proportions inferred by STRUCTURE

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publicJul 2020View details →
dryad28/100

Data from: Genetic drift outweighs natural selection at toll-like receptor (TLR) immunity loci in a reintroduced population of a threatened species

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publicJun 2013View details →
dryad28/100

Data from: Ecological drift and the distribution of species diversity

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publicApr 2017View details →
dryad28/100

Data from: Evolution of drift robustness in small populations

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publicJun 2018View details →
dryad28/100

Data from: Fixation of mutators in asexual populations: the role of genetic drift and epistasis

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publicOct 2012View details →
dryad28/100

Data from: Population genomics of the killer whale indicates ecotype evolution in sympatry involving both selection and drift

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publicSep 2014View details →
dryad28/100

Data from: Inbreeding depression and drift load in small populations at demographic disequilibrium

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publicNov 2016View details →
nasa28/100

Daily Arctic Ocean Rawinsonde Data from Soviet Drifting Ice Stations, Version 1

This archive of daily rawinsonde measurements of wind direction and speed, atmospheric pressure, humidity, air temperature, and geopotential height as well as surface-based observation of cloud cover (amount, type and height) from Soviet North Pole drifting stations was assembled under the direction of Dr. J. Kahl, with funding from the National Oceanic and Atmospheric Administration, the National Science Foundation, and the Electric Power Research Institute. Soundings were recorded from April 19, 1954 to July 31, 1990 at drifting stations located in the Arctic Ocean, north of approximately 70 degrees North. Data were obtained from several different sources. All of these data are ultimately derived from the set of bound volumes of handwritten tables kept at the Arctic and Antarctic Research Institute (AARI) in St. Petersburg, Russia. Data are in 21 ASCII text format files with an average size of under 10 MB.

restrictednotspecifiedApr 2025View details →
nasa28/100

IPAB Antarctic Drifting Buoy Data, Version 1

Through participating research organizations in various countries, the World Climate Research Programme's (WCRP) International Programme for Antarctic Buoys (IPAB) maintains a network of drifting buoys in the Antarctic sea ice zone to support a better understanding of sea ice motion, meteorology, and oceanography. The IPAB Antarctic Drifting Buoy Data archive, spanning the years 1995 to 1998, includes measurements of buoy position, atmospheric pressure, air temperature, and sea surface temperature. Data are organized by daily and three-hour averages and are provided as raw, instantaneous, non-interpolated data values. Data were collected from buoys initially deployed in the following three study regions: East Antarctica; the Weddell Sea; and the Bellingshausen, Amundsen, and Ross Seas.

restrictednotspecifiedApr 2025View details →
dryad24/100

Data from: Genetic drift and collective dispersal can result in chaotic genetic patchiness

Chaotic genetic patchiness denotes unexpected patterns of genetic differentiation that are observed at a fine scale and are not stable in time. These patterns have been described in marine species with free-living larvae, but are unexpected because they occur at a scale below the dispersal range of pelagic larvae. At the scale where most larvae are immigrants, theory predicts spatially homogeneous, temporally stable genetic variation. Empirical studies have suggested that genetic drift interacts with complex dispersal patterns to create chaotic genetic patchiness. Here we use a coancestry model and individual-based simulations to test this idea. We found that chaotic genetic patterns (qualified by global FST and spatio-temporal variation in FST's between pairs of samples) arise from the combined effects of (1) genetic drift created by the small local effective population sizes of the sessile phase and variance in contribution among breeding groups and (2) collective dispersal of related individuals in the larval phase. Simulations show that patchiness levels qualitatively comparable to empirical results can be produced by a combination of strong variance in reproductive success and mild collective dispersal. These results call for empirical studies of the effective number of breeders producing larval cohorts, and population genetics at the larval stage.

opencc-zeroDec 2011View details →
zenodo24/100

SCB model data for article 'The effects of localized thermal pressure on equilibrium magnetic fields and particle drifts in the inner magnetosphere'

<p>The SCB model simulation data for the article&nbsp;&#39;The effects of localized thermal pressure on equilibrium magnetic fields and particle drifts in the inner magnetosphere&#39;.</p> <p>The &#39;Rxx_A xx_Sxx_Lxxparameters&#39; files are the data files, where Rxx is the beta_0 value, Axx is the A_e value, Sxx is the sigma_0 value and Lxx is the L_0 value (see the article for the definition of the values)</p> <p>The &#39;SCB_variables.xlsx&#39; is a table to describe the variables in the data file.</p> <p>The &#39;read_scb.pro&#39; is an IDL program to read the data files.</p>

opencc-by-4.0Apr 2019View details →
dryad24/100

Data from: Genetic drift and collective dispersal can result in chaotic genetic patchiness

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publicOct 2012View details →
nasa24/100

First ISCCP Regional Experiment (FIRE) Atlantic Stratocumulus Transition Experiment (ASTEX) SOFIA Drifting Buoy Data

The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.SOFIA (Surface of the Ocean, Fluxes and Interaction with the Atmosphere) is a research program carried out by French groups from the Centre de Recherches en Physique de l'Environnement (CRPE), Laboratoire l'Aerologie (LA)-Toulouse, Centre de Meteorologie Marine (CMM)-Brest, Institut Francais de Rechercher sur la Mer (IFREMER)-Brest, Service d'Aeronomie-Paris, and Laboratoire de Meteorologie Dynamique (LMD)-Palaiseau with cooperation from Centre National de Recherche Meteorologique (CNRM)-Toulouse.The scientific objective of SOFIA during ASTEX was the study of energy transfer (heat, humidity and momentum fluxes) between the sea surface and the atmospheric boundary layer at scales ranging from the local scale to the mesoscale (50 km). The general concept of the program was to develop a measurement strategy based on nested boxes in which instrumentation would be used to estimate and quantify fluxes. These instruments, from which flux estimates at different scales would be measured, were used in connection with satellite measurements to understand and, hence, to validate the satellite integration of fluxes, particularly in the presence of mesoscale oceanic andatmospheric structures responsible for spatial inhomogeneity of fluxes.Five drifting buoys (CMM) with bathymetric chains (100 m) provided surface measurements of sea surface temperature, pressure and wind.

restrictednotspecifiedApr 2025View details →
nasa20/100

MMS 4 Electron Drift Instrument (EDI) Quality 0 Counts, Level 2 (L2), Burst Mode, 7.8125 ms Data

Electron Drift Instrument (EDI) Q0 Burst Survey, Level 2, 0.0078125 s Data (128 samples/s). EDI has two scientific data acquisition modes, called electric field mode and ambient mode. In electric field mode, two coded electron beams are emitted such that they return to the detectors after one or more gyrations in the ambient magnetic and electric field. The firing directions and times-of-flight allow the derivation of the drift velocity and electric field. In ambient mode, the electron beams are not used. The detectors with their large geometric factors and their ability to adjust the field of view quickly allow continuous sampling of ambient electrons at a selected pitch angle and fixed but selectable energy. To find the beam directions that will hit the detector, EDI sweeps each beam in the plane perpendicular to B at a fixed angular rate of 0.22 °/ms until a signal has been acquired by the detector. Once signal has been acquired, the beams are swept back and forth to stay on target. Beam detection is not determined from the changes in the count-rates directly, but from the square of the beam counts divided by the background counts from ambient electrons, i.e., from the square of the instantaneous signal-to-noise ratio (SNR). This quantity is computed from data provided by the correlator in the Gun-Detector Electronics that also generates the coding pattern imposed on the outgoing beams. If the squared SNR ratio exceeds a threshold, this is taken as evidence that the beam is returning to the detector. The thresholds for SNR are chosen dependent on background fluxes. They represent a compromise between getting false hits (induced by strong variations in background electron fluxes) and missing true beam hits. The basic software loop that controls EDI operations is executed every 2 ms. As the times when the beams hit their detectors are neither synchronized with the telemetry nor equidistant, EDI data have no fixed time-resolution. Data are reported in telemetry slots. In Survey, using the standard packing mode 0, there are eight telemetry slots per second and Gyn Detector Unit (GDU). The last beam detected during the previous slot will be reported in the current slot. If no beam has been detected, the data quality will be set to zero. In Burst telemetry there are 128 slots per second and GDU. The data in each slot consists of information regarding the beam firing directions (stored in the form of analytic gun deflection voltages), times-of-flight (if successfully measured), quality indicators, time stamps of the beam hits, and some auxiliary correlator-related information. Whenever EDI is not in electron drift mode, it uses its ambient electron mode. The mode has the capability to sample at either 90 degrees pitch angle or at 0/180 degrees (field aligned), or to alternate between 90 degrees and field aligned with selectable dwell times. While all options have been demonstrated during the commissioning phase, only the field aligned mode has been used in the routine operations phase. The choices for energy are 250 eV, 500 eV, and 1 keV. The two detectors, which are facing opposite hemispheres, are looking strictly into opposite directions, so while one detector is looking along B the other is looking antiparallel to B (corresponding to pitch angles of 180 and 0 degrees, respectively). The two detectors switch roles every half spin of the spacecraft as the tip of the magnetic field vector spins outside the field of view of one detector and into the field of view of the other detector. These data are a by-product generated from data collected in electric field mode. Whenever no return beam is found in a particular time slot by the flight software to be reported will be flagged with the lowest quality level (quality zero). The ground processing generates a separate data product from these counts data. The EDI instrument paper can be found at: http://link.springer.com/article/10.1007%2Fs11214-015-0182-7. The EDI instrument data products guide can be found at https://lasp.colorado.edu/mms/sdc/public/datasets/fields/.

restrictednotspecifiedAug 2025View details →
nasa20/100

MMS 3 Electron Drift Instrument (EDI) Ambient Electron Flux, Projection Method 1 (PM1), Level 2 (L2), Burst Mode, 0.9765625 ms Data

Electron Drift Instrument (EDI) Ambient Burst Survey, Level 2, 0.0009765625 s Data (1024 samples/s). EDI has two scientific data acquisition modes, called electric field mode and ambient mode. In electric field mode, two coded electron beams are emitted such that they return to the detectors after one or more gyrations in the ambient magnetic and electric field. The firing directions and times-of-flight allow the derivation of the drift velocity and electric field. In ambient mode, the electron beams are not used. The detectors with their large geometric factors and their ability to adjust the field of view quickly allow continuous sampling of ambient electrons at a selected pitch angle and fixed but selectable energy. To find the beam directions that will hit the detector, EDI sweeps each beam in the plane perpendicular to B at a fixed angular rate of 0.22 °/ms until a signal has been acquired by the detector. Once signal has been acquired, the beams are swept back and forth to stay on target. Beam detection is not determined from the changes in the count-rates directly, but from the square of the beam counts divided by the background counts from ambient electrons, i.e., from the square of the instantaneous signal-to-noise ratio (SNR). This quantity is computed from data provided by the correlator in the Gun-Detector Electronics that also generates the coding pattern imposed on the outgoing beams. If the squared SNR ratio exceeds a threshold, this is taken as evidence that the beam is returning to the detector. The thresholds for SNR are chosen dependent on background fluxes. They represent a compromise between getting false hits (induced by strong variations in background electron fluxes) and missing true beam hits. The basic software loop that controls EDI operations is executed every 2 ms. As the times when the beams hit their detectors are neither synchronized with the telemetry nor equidistant, EDI data have no fixed time-resolution. Data are reported in telemetry slots. In Survey, using the standard packing mode 0, there are eight telemetry slots per second and Gyn Detector Unit (GDU). The last beam detected during the previous slot will be reported in the current slot. If no beam has been detected, the data quality will be set to zero. In Burst telemetry there are 128 slots per second and GDU. The data in each slot consists of information regarding the beam firing directions (stored in the form of analytic gun deflection voltages), times-of-flight (if successfully measured), quality indicators, time stamps of the beam hits, and some auxiliary correlator-related information. Whenever EDI is not in electron drift mode, it uses its ambient electron mode. The mode has the capability to sample at either 90 degrees pitch angle or at 0/180 degrees (field aligned), or to alternate between 90 degrees and field aligned with selectable dwell times. While all options have been demonstrated during the commissioning phase, only the field aligned mode has been used in the routine operations phase. The choices for energy are 250 eV, 500 eV, and 1 keV. The two detectors, which are facing opposite hemispheres, are looking strictly into opposite directions, so while one detector is looking along B the other is looking antiparallel to B (corresponding to pitch angles of 180 and 0 degrees, respectively). The two detectors switch roles every half spin of the spacecraft as the tip of the magnetic field vector spins outside the field of view of one detector and into the field of view of the other detector. Up until January 4, 2016 the anodes were chosen such that the magnetic field vector projected into the plane of the micro-channel plate entry surface was best aligned with the center of the four anodes ( that is, with the gap between the inner two of the four anodes). Data taken in this configuration are using the term "amb" in the data product names. In the burst data where four channels (corresponding to the four adjacent sensor anode pads) are sampled per GDU, the average (or sum) of the center two channels (channels 2 and 3) represents best the pitch angle of 0 degrees (or 180 degrees). The EDI instrument paper can be found at: http://link.springer.com/article/10.1007%2Fs11214-015-0182-7. The EDI instrument data products guide can be found at https://lasp.colorado.edu/mms/sdc/public/datasets/fields/.

restrictednotspecifiedAug 2025View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record