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2,139 results for “recognition”
Asymmetric song recognition does not influence gene flow in an emergent songbird hybrid zone
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Data from: The CellPhe toolkit for cell phenotyping using time-lapse imaging and pattern recognition
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The human origin recognition complex (ORC) is essential for pre-RC assembly, mitosis and maintenance of nuclear structure
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Evidence for individual vocal recognition in a pair-bonding poison frog, Ranitomeya imitator
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Rapid resource depletion on coral reefs disrupts competitor recognition processes among butterflyfish species
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A review of Appalachian Dasycerus Brongniart, and the recognition of cryptic diversity within Dasycerus carolinensis Horn (Coleoptera: Staphylinidae: Dasycerinae)
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EMG dataset for gesture recognition with arm translation
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Dataset for worker activity recognition and efficiency estimation during manual harvesting
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Activity recognition from in-the-wild smartwatches (ArWISE)
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Data from: Evidence for a selective link between cooperation and individual recognition
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Data for: Kin recognition for incest avoidance in Damaraland mole-rats, Fukomys damarensis
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Not so weak-PICO: Leveraging weak supervision for Participants, Interventions, and Outcomes recognition for systematic review automation
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Data from: Both learning and syntax recognition are used by great tits when answering to mobbing calls
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The Structural Basis of the Genetic Code: Amino Acid Recognition by Aminoacyl-tRNA Synthetases
<p>Data sets for the characterization of amino acid recognition in aminoacyl-tRNA synthetases:</p> <ul> <li>multiple-sequence alignment files in FASTA format</li> <li>Excel tables to infer original sequence positions from renumbered positions</li> </ul> <p>Accompanying the paper: <a href="https://www.biorxiv.org/content/10.1101/606459v1">https://www.biorxiv.org/content/10.1101/606459v1</a></p>
Emotion recognition HD - Data and R code
<p>Data and R code - <strong>Recognition of emotion from subtle and non-stereotypical dynamic facial expressions in Huntington's diseaseRecognition of emotion from subtle and non-stereotypical dynamic facial expressions in Huntington's disease</strong></p>
EMG and Video Dataset for sensor fusion based hand gestures recognition
<p>This dataset contains data for hand gesture recognition recorded with 3 different sensors. </p> <p>sEMG: recorded via the Myo armband that is composed of 8 equally spaced non-invasive sEMG sensors that can be placed approximately around the middle of the forearm. The sampling frequency of Myo is 200 Hz. The output of the Myo is a.u </p> <p>DVS: Dynamic Video Sensor which is a very low power event-based camera with 128x128 resolution</p> <p>DAVIS: Dynamic Video Sensor which is a very low power event-based camera with 240x180 resolution that also acquires APS frames.</p> <p>The dataset contains recordings of 21 subjects. Each subject performed 3 sessions, where each of the 5 hand gesture was recorded 5 times, each lasting for 2s. Between the gestures a relaxing phase of 1s is present where the muscles could go to the rest position, removing any residual muscular activation.</p> <p> </p> <p>Note: All the information for the DVS sensor has been extracted and can be found in the *.npy files. In case the raw data (.aedat) was needed please contact</p> <p> </p> <p>enea.ceolini@ini.uzh.ch</p> <p>elisa@ini.uzh.ch</p> <p>==== README ====</p> <p> </p> <p>DATASET STRUCTURE:</p> <p>EMG, DVS and APS recordings</p> <p>21 subjects</p> <p>3 sessions for each subject</p> <p>5 gestures in each session ('pinky', 'elle', 'yo', 'index', 'thumb')</p> <p> </p> <p>SINGLE DATASETS:</p> <p>- relax21_raw_emg.zip: contains raw sEMG and annotations (ground truth of gestures) in the format `subjectXX_sessionYY_ZZZ` with `XX` subject ID (01 to 21), `YY` session ID (01-03) and `ZZZ` that can be ‘emg’ or ‘ann’.</p> <p> </p> <p>- relax21_raw_dvs.zip: contains the full-frame dvs events in an array with dimensions 0 -> addr_x, 1 -> addr_y, 2 -> timestamp, 3 -> polarity. The timestamps are in seconds and synchronized with the Myo. Each file is in the format `subjectXX_sessionYY_dvs` with `XX` subject ID (01 to 21), `YY` session ID (01-03).</p> <p> </p> <p>- relax21_cropped_aps.zip: contains the 40x40 pixel aps frames for all subjects and trials in the format `subjectXX_sessionYY_Z_W_K` with `XX` subject ID (01 to 21), `YY` session ID (01-03), Z gesture ('pinky', 'elle', 'yo', 'index', 'thumb’), W trial ID (1-5), `K` frame index.</p> <p> </p> <p>- relax21_cropped_dvs_emg_spikes.pkl: spiking dataset that can be used to reproduce the results in the paper. The dataset is a dictionary with the following keys:</p> <ul> <li><strong>- </strong><strong>y</strong>: array of size 1xN with the class (0->4).</li> <li><strong>- </strong><strong>sub</strong>: array of size 1xN with the subject id (1->10).</li> <li><strong>- </strong><strong>sess</strong>: array of size 1xN with the session id (1->3).</li> <li><strong>- </strong><strong>dvs</strong>: list of length N, each object in the list is a 2d array of size 4xT_n where T_n is the number of events in the trial and the 4 dimensions rappresent: 0 -> addr_x, 1 -> addr_y, 2 -> timestamp, 3 -> polarity .</li> <li><strong>- </strong><strong>emg</strong>: list of length N, each object in the list is a 2d array of size 3xT_n where T_n is the number of events in the trial and the 3 dimensions rappresent: 0 -> addr, 1 -> timestamp, 3 -> polarity.</li> </ul> <p> </p> <p> </p>
Figure 5. Dorsal habitus, P in The Platycerus (Coleoptera, Lucanidae) of California, with the recognition of Platycerus cribripennis Van Dyke as a valid species
Figure 5. Dorsal habitus, P. oregonensis male.
Figure 4. Dorsal habitus, P in The Platycerus (Coleoptera, Lucanidae) of California, with the recognition of Platycerus cribripennis Van Dyke as a valid species
Figure 4. Dorsal habitus, P. marginalis male.
Figure 3. Dorsal habitus, P in The Platycerus (Coleoptera, Lucanidae) of California, with the recognition of Platycerus cribripennis Van Dyke as a valid species
Figure 3. Dorsal habitus, P. cribripennis male.
Molecular recognition and dynamics of linear poly-ubiquitins: integrating coarse-grain simulations and experiments
<p>Poly-ubiquitin chains are flexible multidomain proteins, whose conformational dynamics enable their molecular recognition by a large number of partners in multiple biological pathways. By using alternative linkage, it is possible to obtain poly-ubiquitin molecules with different dynamical properties. This flexibility is further increased by the possibility to tune the length of poly-ubiquitin chains. Characterizing the dynamics of poly-ubiquitins as a function of their length is thus relevant to understand their biology. Structural characterization of poly-ubiquitin conformational dynamics is challenging both experimentally and computationally due to increasing system size and conformational variability. Here, by developing highly efficient and accurate small-angle X-ray scattering driven Martini coarse-grain simulations, we characterize the dynamics of linear M1-linked di-, tri- and tetra-ubiquitin chains. Our data show that the behavior of the di-ubiquitin subunits is independent of the presence of additional ubiquitin modules. We propose that the conformational space sampled by linear poly-ubiquitins, in general, may follow a simple self-avoiding polymer model. These results, combined with experimental data from small angle X-ray scattering, biophysical techniques and additional simulations show that binding of NEMO, a central regulator in the NF-κB pathway, to linear poly-ubiquitin obeys a 2:1 (NEMO:poly-ubiquitin) stoichiometry in solution, even in the context of four ubiquitin units. Eventually, we show how the conformational properties of long poly-ubiquitins may modulate the binding with their partners in a length-dependent manner.</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.