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7,518 results for “screenings”
Non-target screening of a Siberian ice core reveals changes in the pre-industrial to industrial organic aerosol composition
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Data from: Genome-wide CRISPR synthetic lethality screen identifies a role for the ADP-ribosyltransferase PARP14 in replication fork stability controlled by ATR
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Data from: Epigenetic small molecule screening identifies a new HDACi compound for ameliorating Duchenne muscular dystrophy
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Code for: Multi-modal screening for synergistic neuroprotection of mild extremely preterm brain injury: Cell counting code repository
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Spatial targeting of Screening + Eave tubes (SET), a house-based malaria control intervention, in Côte d’Ivoire: A geostatistical modelling study
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The docked poses from the docking screens against the AlphaFold2 models of the σ2 and 5HT2A receptors
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Data reported in development and cross-validation of a veterans mental health risk factor screen
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Data from: COPD screening using time–frequency features of self-recorded respiratory sounds
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Iterative evaluation of mobile computer-assisted digital chest x-ray screening for TB improves efficiency, yield, and outcomes in Nigeria
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CRISPR/Cas9 screen for essential endolysosomal genes under free choline limitation
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Highly-multiplexed mass cytometry screen of human bone marrow hematopoietic stem and progenitor cells
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Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity
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Proteome-wide microarray-based screening of PAR-binding proteins
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Human RAD54 inhibitor screen: summary of 158 compounds identified as 'hits'
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Compound Interest: Discussing the EU Open Screen Project at the MDC
<p><strong>Episode Summary</strong></p> <p>In this episode we talk to Dr. Jens Peter von Kries and Dr Katja Herzog from the Max-Delbrück-Center for Molecular Medicine (MDC) about their work on the open access technology platform EU Open Screen Project. </p> <p><strong>Episode Links</strong></p> <p><a href="https://www.mdc-berlin.de/screening-unit">EU Open Screen MDC</a></p> <p><a href="https://www.eu-openscreen.eu/">EU Open Screen </a></p> <p><strong>Quotes</strong></p> <p>"From bench to bedside, this really shows that from academia there is really a chance to help people in the clinics"</p>
Machine learning in mass spectrometry: A MALDI-TOF MS approach to phenotypic antibacterial screening
<p>Dataset relating to the publication:</p> <p>Machine learning in mass spectrometry: A MALDI-TOF MS approach to phenotypic antibacterial screening</p> <p>by Luuk Nico van Oosten and Christian D. Klein</p> <p>Published in the Journal of Medicinal Chemistry, 2020</p> <p><strong>Important notice:</strong></p> <p><strong>The data are free to use for non-commercial, academic purposes, provided that the original source is<br> cited and the authors and the publication are credited in any derivative work.</strong></p> <p><strong>A patent application has been filed for the method described by van Oosten and Klein, which uses mass<br> spectrometry and machine learning to identify the pharmacological or other effects of compounds on cell<br> cultures and other biological systems.</strong></p> <p>Therefore, a license for the commercial use of the method must be negotiated by contacting either</p> <p>Anke Faller<br> Universität Heidelberg<br> Dezernat Forschung<br> Rechts- und Strukturfragen der Forschungsförderung<br> Seminarstraße 2, 69117 Heidelberg<br> Tel. +49 6221 54-12611<br> anke.faller(at)zuv.uni-heidelberg.de</p> <p>or</p> <p>Prof. Dr. C. Klein; c.klein(at)uni-heidelberg.de<br> Medicinal Chemistry<br> Institute of Pharmacy and Molecular Biotechnology IPMB<br> Heidelberg University, INF 364<br> D-69120 Heidelberg<br> Germany<br> Phone: ++49-6221-54-4875<br> FAX : ++49-6221-54-6430</p> <p> </p>
Development of a novel system of screening for hypoxia tolerance in barley
<p>Dataset containing the growth of barley under hypoxic conditions, controls, controls using rye, RNA yields and gene expression</p>
Replication Package: UI Screens Identification and Extraction from Mobile Programming Screencasts
<p>The replication package of the paper "UI Screens Identification and Extraction from Mobile Programming Screencasts" including the dataset, results, and code.</p>
The V2S Dataset: A Set of Android Screen Recordings, Training Images, and Models
<p>This is the dataset and models used in the paper entitled "Translating Video Recordings of Mobile App Usages into Replayable Scenarios" published at the 42nd International Conference on Software Engineering (ICSE'20)</p> <p>Link to V2S Paper: https://arxiv.org/abs/2005.09057</p>
Statistical characterisation and responses of acoustic screens and two-layers systems
<p>The present dataset contains measurements of the acoustic response of screens in an impedance tube with different backings. It includes as well the characterised parameters for the screens and backings.</p> <p><strong>License</strong></p> <p>This dataset is released under Creative Commons with Attribution (CC BY). Any reutilisation of the present dataset in scholarly works must properly cite this work and its authors:</p> <pre><code>Statistical characterisation and responses of acoustics screens and two-layers systems M. Gaborit, L. Jaouen, O. Dazel, P. Göransson DOI: 10.5281/zenodo.3358921 </code></pre> <p><strong>Protocol</strong></p> <p>Two different films (one woven and one non-woven) were sampled 40 times in order to characterise their parameters in an impedance tube. Sampling is manual, the tube inner diameter is 44.44mm and the samples are cut to a slightly large size in order to be clamped inside the tube for measurements.</p> <p>The films are tested in different configurations including some with backings. Two types of backings are considered (melamine and glass wool). These backings are also characterised using 3 and 2 samples respectively. When measuring the response of the film on a backing only 20 samples of each film were used.</p> <p>All measurements span the [4, 4520] Hz band. The setup is calibrated anew before each measurement session.</p> <p><strong>Films' characterisation</strong></p> <p>The films are clamped in the seam between the two parts of the tube, a 200mm air plenum is formed downstream and ends with a rigid backing. The samples for each type of film are measured within 4h.</p> <p>The characterisation procedure implements the method described in the following reference:</p> <ul> <li>Jaouen L. Bécot F.-X. JASA 129(3) pp. 1400 - 1406, 2011</li> </ul> <p><strong>Backings' characterisation</strong></p> <p>The sample and backing piston are placed to give a rigid backing and have the sample's surface flush with the seam between the two parts of the tube. In the case of the glass wool, the material has a slight (below millimetre) embossing and the supporting surface is placed flush with respect to the seam (the top of the embossing is not considered as the sample surface).</p> <p>The characterisation procedure implements the method described in the following references:</p> <ul> <li>Olny, X. & Panneton, R. JASA 123(2) pp. 814 – 824, 2008</li> <li>Panneton R. & Olny, X. JASA 119(4), p. 2027, 2006</li> </ul> <p><strong>Response measurements</strong></p> <p>To measure responses of the film/backing systems, the backing are placed as described in the previous paragraph. The film is clamped in the seam as described in the "Films' characterisation" section. A plastic grid with thin struts is placed upstream to prevent the film from bending. This setup allows for easily changing the film without replacing the backing sample. Films' samples 1 to 20 are used for response measurements. Measurement of the grid response on a rigid backing and an air plenum of 200mm are provided for reference.</p> <p><strong>Hardware</strong></p> <ul> <li><a href="http://www.mecanum.com/en/products/impedance-tube/impedance-and-transmission-tube-3-mic/">Mecanum 3-microphones tube, diameter: 44.44mm</a></li> </ul> <p><strong>Software</strong></p> <ul> <li><a href="http://tubecell.matelys.com/">Matelys TubeCell</a> (rig control)</li> <li><a href="http://rokcell.matelys.com/">Matelys RoKCell</a> (characterisation)</li> </ul> <p>The piece of software controlling the rig implements a 3-microphones technique described in the following references:</p> <ul> <li>Iwase T. Izumi Y. J. Acoust. Soc. Jpn J 52(6) pp. 411–419, 1996 (in Japanese)</li> <li>Iwase T. Izumi Y. Kawabata R. in proc. Internoise, 1998 (Christchurch, New Zealand)</li> </ul> <p><strong>Structure of the datasets and files</strong></p> <p>The present dataset comprises two parts. The actual traces and associated measurement parameters as exported from TubeCell are found in the directory <code>measurements</code>. The results from the characterisation process as exported with RoKCell are in the <code>characterisations</code> folder. These results were augmented with direct measurements of the weights and thickness of the samples (both for the films and the backings).</p> <p><strong>Measurements</strong></p> <p>The measurements are stored in the <code>measurements</code> directory. There are several sub-directory for each of the measurement sessions:</p> <ul> <li><code>backings</code>: measurements for the caracterisation of the two backings (all samples, with and without grid)</li> <li><code>grid</code>: measurements of the grid alone on a rigid backing and with a 200mm air plenum</li> <li><code>nonwoven_alone</code>: measurements for the caracterisation of the non-woven film on a 200mm air plenum, no grid (all 40 samples)</li> <li><code>woven_alone</code>: measurements for the caracterisation of the woven film on a 200mm air plenum, no grid (all 40 samples)</li> <li><code>nonwoven_on_glasswool</code>: measurements of the response of 20 non-woven film samples clamped with a grid upstream and the same glass wool sample downstream on a rigid backing</li> <li><code>nonwoven_on_melamine</code>: measurements of the response of 20 non-woven film samples clamped with a grid upstream and the same melamine sample downstream on a rigid backing</li> <li><code>woven_on_glasswool</code>: measurements of the response of 20 woven film samples clamped with a grid upstream and the same glass wool sample downstream on a rigid backing</li> <li><code>woven_on_melamine</code>: measurements of the response of 20 woven film samples clamped with a grid upstream and the same melamine sample downstream on a rigid backing</li> </ul> <p>Each measurement is stored into a <code>.irk</code> <em>and</em> a <code>.rok</code> file. The first one contains some meta-data on the measurement process, the second contains the actual traces.</p> <p><strong>Structure of irk files</strong></p> <p>The <code>.irk</code> files contain the following meta-data:</p> <ul> <li>Date</li> <li>Medium ID</li> <li>Thickness</li> <li>Size of the air plenum</li> <li>Measure parameter l</li> <li>Measure parameter s</li> <li>Sampling frequency</li> <li>Tube radius [m]</li> <li>Average 1</li> <li>Average 2</li> <li>Temperature [°C]</li> <li>Atmospheric pressure [Pa]</li> <li>Humidity [%]</li> <li>High cut-off frequency (generator) [Hz]</li> <li>Low cut-off frequency (generator) [Hz]</li> <li>Position of the cavity microphone</li> <li>Comments</li> </ul> <p><strong>Structure of rok files</strong></p> <p>The <code>.rok</code> files contain the following vector (column-major). The first line is to be omitted when reading the files, it contains the columns title. The columns are these:</p> <ul> <li>Frequency (Hz)</li> <li>Absorption coefficient</li> <li>Real part of the reflection coefficient</li> <li>Imaginary part of the reflection coefficient</li> <li>Real part of the normalised surface impedance</li> <li>Imaginary part of the normalised surface impedance</li> <li>Real part of the transfer function</li> <li>Imaginary part of the transfer function</li> <li>Real part of the normalised density</li> <li>Imaginary part of the normalised density</li> <li>Real part of the normalised compressibility</li> <li>Imaginary part of the normalised compressibility</li> <li>... frequency response functions used to compute the previous quantities</li> </ul> <p><strong>Characterisations</strong></p> <p>The directory <code>characterisations</code> contains YAML 1.2 files created from the output files of the characterisation software, exploiting the measurement data. There are three subdirectories:</p> <ul> <li><code>backings</code> contains the characterisation of the backings (each sample and an average file)</li> <li><code>nonwoven</code> contains the characterisation of the non-woven film (each sample and an average file)</li> <li><code>woven</code> contains the characterisation of the woven film (each sample and an average file)</li> </ul> <p><strong>More information</strong></p> <p>For further inquiry write to gaborit at kth dot se</p>
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.