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13,405 results for “targets”
S56 | UOATARGPHARMA | Target Pharmaceutical/Drug List from University of Athens
<p>This is the dataset associated with list S56 UOATARGPHARMA on the NORMAN Suspect List Exchange:</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p>
S53 | UFZWANATARG | Target Compounds from UFZ WANA
<p>This is the collection associated with list S53 UFZWANATARG on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>List of target compounds (LC and GC) measured at WANA, UFZ (Leipzig, Germany), provided by Tobias Schulze and Martin Krauss.</p>
Table S27: Target and identified unknown organic micropollutants detected in surface water samples taken during heavy rain events
<p>In the following table, peak intensities of detected organic micropollutants in water samples are displayed.</p> <p>This data table is part of the appendix of Chapter 4 of the PhD thesis “Novel approaches to identify drivers of chemical stress in small rivers” by Liza-Marie Beckers prepared at RWTH Aachen University and at the Helmholtz Centre for Environmental Research-UFZ. In Chapter 4, precipitation-related pollutant patterns and indicator compounds during heavy rain events were identified in the Holtemme River by nontarget screening and cluster analysis. The table contains peak heights of organic micropollutants detected in water samples taken during heavy rain events in the Holtemme River (Saxony – Anhalt, Germany). The table is structured into the following columns: Compound name, use class of compound (e.g., pharmaceutical or pesticide), distinction between target or identified unknown compounds, mass-to-charge ratio (m/z), retention time (RT), assignment to a pattern identified by cluster analysis (i.e., “Base” or “Quick”), the probability of belonging to the assigned pattern as number between 0 and 1 as well as the peak height of the compound in each sample. The samples are indicated by "B" for "bottle" and a number from 1-16. The use class “NA” indicates that now major use class for this compound could be identified.</p> <p>The sampling was triggered by combined sewer overflow at a wastewater treatment plant upstream of the sampling point. Samples were taken by an automated sampler in 30-min composite samples for 8 hours resulting in 16 samples per rain event. In total, 6 heavy rain events from May to September 2016 were sampled during this study. The table is divided into 6 subtables (i.e., Table S27 A-F). Each subtable displays compounds and their peak heights detected in samples from one heavy rain event. The different rain events are abbreviated by the sampling date:</p> <p>Table S27A displays results from the rain event samples May 29<sup>th</sup> 2016 : E2905</p> <p>Table S27B displays results from the rain event samples June 01<sup>st</sup> 2016 : E0106</p> <p>Table S27C displays results from the rain event samples June 24<sup>th</sup> 2016 : E1306</p> <p>Table S27D displays results from the rain event samples June 13<sup>th</sup> 2016 : E2406</p> <p>Table S27E displays results from the rain event samples July 13<sup>th</sup> 2016 : E1307</p> <p>Table S27F displays results from the rain event samples September 17<sup>th</sup> 2016 : E1709</p> <p>Chemical analysis of the water samples was performed by liquid chromatography (UltiMate 3000 LC system (Thermo Scientific)) coupled to high resolution mass spectrometry (Q Exactive Plus, Thermo Scientific) with a heated electrospray ionization (HESI) source. Nontarget screening was performed as it allows for a comprehensive characterization of the chemical exposure during heavy rain events. However, only annotated target compounds and unknown compounds identified by structure elucidation are presented in the table. Details on data evaluation methods are described in Chapter 4 of the PhD thesis.</p> <p>Beckers, L.M. (2019): Novel approaches to identify drivers of chemical stress in small rivers. RWTH Aachen University, Aachen.</p>
Multi-omic Insights into Molecular Mechanism and Therapeutic Targets in Spinocerebellar Ataxia type 7
<p>The molecular mechanism in spinocerebellar ataxia type 7 is currently poorly understood. To provide understandings, a multi-omic study was performed using SCA7266Q/5Q mice. At week 12, entire brain tissue samples were collected and RNA sequencing, methylation analysis, and proteomic analysis were performed. Results were integrated to identify genes with identical trends in expression. Data was also compared with SCA patient serum proteomic analysis, and based on common differentially expressed proteins, a Naïve Bayesian network model was constructed to predict nilotinib treatment response. Data from RNA sequencing and methylation analysis revealed 58 significantly hypomethylated-upregulated genes and 62 hypermethylated-downregulated genes, mostly enriched in GO terms of regulation of axonogenesis, channel activity, and monoamine signaling. In the proteomic analysis, 211 upregulated and 281 downregulated DEPs associated mostly with immune response and cellular mobility were identified. Two genes, Fam107b and Tph2, showed differential expression in both transcriptomic and proteomic analysis. Forty-two overlapping proteins were identified compared with SCA patient serum, and Bayesian network analysis revealed that nilotinib treatment response was associated with the protein expression of CLU, CA2, GLUL, PRDX6, C1QA, PLXNB1, and age. These findings will serve as an important reference for future studies on the pathogenesis and discovery of druggable targets. </p>
Graphic Illustration of Neal Platt's Talk: Targeted sequencing of pathogen DNA from museum specimens
<p><a href="https://lib.ku.edu/people/courtney-foat" target="_blank" rel="noopener">Courtney Foat</a>, Advisor for Strategic Initiatives & Organizational Engagement at the University of Kansas, graphically recorded this invited talk by Neal Platt at an NSF-supported Workshop: Digital Collections Data and Tracking Disease.</p>
Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain - Datasets and Python notebooks
<p>This dataset and the associated Python notebooks and R-code are related to the publication "Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain".</p>
MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music
<p>The <em><strong>MAD-EEG Dataset</strong></em> is a research corpus for studying EEG-based auditory attention decoding to a target instrument in polyphonic music. </p> <p>The dataset consists of 20-channel EEG responses to music recorded from 8 subjects while attending to a particular instrument in a music mixture. </p> <p>For further details, please refer to the paper: <em><a href="https://hal.archives-ouvertes.fr/hal-02291882/document">MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music</a>.</em></p> <p>If you use the data in your research, please reference the paper (not just the Zenodo record):</p> <pre><code>@inproceedings{Cantisani2019, author={Giorgia Cantisani and Gabriel Trégoat and Slim Essid and Gaël Richard}, title={{MAD-EEG: an EEG dataset for decoding auditory attention to a target instrument in polyphonic music}}, year=2019, booktitle={Proc. SMM19, Workshop on Speech, Music and Mind 2019}, pages={51--55}, doi={10.21437/SMM.2019-11}, url={http://dx.doi.org/10.21437/SMM.2019-11} }</code></pre> <p> </p>
Data from 1564 earthquake/tsunami scenario simulations targeting the Nankai Trough subduction zone
<p><strong>Summary:</strong></p> <ul> <li>Data from 1564 earthquake/tsunami scenario simulations targeting the Nankai Trough subduction zone</li> <li>Tsunami simulation solver: TUNAMI-N2</li> <li>Fault rupture model: Okada model (Okada, 1985)</li> <li>Each scenario data comprises 247 ASCII files storing the simulated wave sequences at synthetic gauges.</li> <li>Every single scenario is tagged as "JNan_X.X_YYY", where X.X indicates the magnitude and YYY is a serial number.</li> <li>Some synthetic gauges are in identical locations to actual ocean gauges (e.g., DONET2, NOWPHAS) near Shikoku, Japan.</li> </ul> <p><strong>Details of each file:</strong></p> <ul> <li><strong>data.tar.gz:</strong> A series of wave sequences (6-hour wave historical data, recorded every 5 seconds) at the 247 virtual gauges. Note that 52 GB of additional storage would be required to fully unzip this archive file with the following command. <pre><code>tar xzvf data.tar.gz</code></pre> <p>The unzipped directory contains all scenario data as follows:</p> <pre><code>data ├── JNan_7.6_001 ├── JNan_7.6_002 ├── JNan_7.6_003 ├── ├── ├── JNan_8.8_326 ├── JNan_8.8_327 └── JNan_8.8_328</code></pre> <p>Each directory contains 247 files named 'pntX_YY.asc'.</p> <pre><code>JNan_X.X_YYY ├── pnt1_01.asc ├── pnt1_02.asc ├── pnt1_03.asc ├── ├── ├── pnt5_46.asc ├── pnt5_47.asc └── pnt5_48.asc</code></pre> <p>In each ASCII file, the time (minute) elapsed from the fault rupture is aligned in the left column, and the wave displacements (meter) from the original sea level are in the right column.</p> </li> <li> <p><strong>quake_params.csv:</strong> The parameter used to generate 1564 earthquake scenarios caused by the rupture of rectangular fault, by means of the Okada model (Okada 1985)</p> </li> <li> <p><strong>synthetic_gauges.csv:</strong> The locations of the 247 synthetic gauges</p> </li> </ul>
The Contributionsof Eye Gaze Fixations and Target-Lure Similarity to Behavioral and fMRI Indices of Pattern Separation and Pattern Completion
Open the record for dataset details and reuse information.
Spectrometer measurements of snow and bare ground targets and simultaneous measurements of snow conditions
<p>The dataset holds measurements of reflected sunlight spectrum from snow and different snow free targets (moss, lichen, rock surface, ground vegetation). The purpose of the measurements has been to create a dataset to better understand the effect of snow cover characteristics and different bare ground targets on reflected sunlight, and to relate this information to observed at satellite reflectances from snow covered and partially snow covered boreal forests. The instrument in the measurements was Field Spec Pro JR from Analytical Spectral Devices Inc. Additionally to the 237 bands measured between 350-2500 nm, the dataset contains the following parameters from the measurement sites: id, location, time of measurement, target type (snow, bare ground etc.), cloudiness (in octas), snow depth (cm), snow temperature at 5 cm (degree C), snow temperature half way through the snow pack (degree C), soil temperature (degree C), air temperature (degree C), average grain size (mm), grain type, snow water content (subjective), snow patchiness (%) in the surrounding area, visible impurities in snow yes/no and land cover.</p>
Measurement of 139La(p,x) cross sections from 35-60 MeV by stacked-target activation
<p>This repository contains all raw gamma-ray spectra analyzed for the present manuscript, as well as calibration spectra. Further details and analysis code are available on reasonable request. </p> <p>A stacked-target of natural lanthanum foils (99.9119% 139La) was irradiated using a 60 MeV proton beam at the LBNL 88-Inch Cyclotron. 139La(p,x) cross sections are reported between 35–60 MeV for nine product radionuclides. The primary motivation for this measurement was the need to quantify the production of 134Ce. As a positron-emitting analogue of the promising medical radionuclide 225Ac, 134Ce is desirable for in vivo applications of bio-distribution assays for this emerging radio-pharmaceutical. The results of this measurement were compared to the nuclear model codes TALYS, EMPIRE and ALICE (using default parameters), which showed significant deviation from the measured values.</p>
predicted microRNA target sites (miRanda)
<p>Target predictions based on the miRanda algorithm. The target sites are scored for likelihood of mRNA downregulation using mirSVR, a regression model that is trained on sequence and contextual features of the predicted miRNA::mRNA duplex. Expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin.</p> <p>This collection contains the following datasets from the August 2010 release of <a href="http://www.microrna.org">microRNA.org</a>:</p> <ul> <li>16228619 predicted microRNA target sites in 34911 distinct 3'UTR from isoforms of 19898 human genes</li> <li>7459149 predicted microRNA target sites in 28287 distinct 3'UTR from isoforms of 19231 mouse genes</li> <li>586068 predicted microRNA target sites in 6865 distinct 3'UTR from isoforms of 6256 rat genes</li> <li>345671 predicted microRNA target sites in 12285 distinct 3'UTR from isoforms of 10532 fruitfly genes</li> </ul>
Data and code to perform the"Target deformation" workflow in R: virtual reconstruction of the Equus stenonis holotype skulll
<p>Data and code to perform the"Target deformation" workflow in R: virtual reconstruction of the Equus stenonis holotype skulll.</p> <p>TargetDeformation.R: R code with for the Target Deformation procedure.<br> IGF560.ply: 3D mesh of the holotype IGF560 in ply extension.<br> IGF560_set.txt: landmark set of the holotype IGF560.<br> Dm. 5/154.3/4.A4.5.ply: 3D mesh of Dm 5/154.3/4.A4.5 in .ply extension.<br> Dm_set.txt: landmark set of the Dm 5/154.3/4.A4.5 sample.<br> IGF11023: 3D mesh of IGF11023 in.ply extension.<br> IGF11023_set.txt: landmark set on the IGF11023 sample.<br> IGF560R: 3D mesh of IGF560R in.ply extension.<br> IGF560W: 3D mesh of IGF560W in.ply extension.<br> IGF560R-s: 3D mesh of IGF560R-s in.ply extension.<br> IGF560W-s: 3D mesh of IGF560W-s in.ply extension.<br> IGF560_IGF560R_IGF560W.html: file that contain WebGL code to reproduce the 3D meshes of IGF560, IGF560R and IGF560W in a browser.<br> IGF560Rs_IGF560Ws.html: file that contain WebGL code to reproduce the 3D meshes of IGF560R-S and IGF560W-S in a browser.<br> IGF560W Mesh area variation.html: file that contain WebGL code to reproduce two 3d meshes of IGF560W using localmeshDist() and meshdist() in a browser.<br> </p>
Word-in-Context Target Sense Verification
<pre>Formally, WiC is framed as a <strong>binary classification</strong> task. Each instance in WiC-TSV consists of a target word <em>w</em> with a corresponding target sense <em>s</em> represented by either its definition (subtask 1) or its hypernym/s (subtask 2), and a context <em>c</em> containing the target word <em>w</em>. The task aims to determine whether the meaning of the word <em>w</em> used in the context <em>c</em> matches the target sense <em>s</em>. In the following table there are some examples from the dataset. </pre> <p> </p> <p>Subtasks</p> <p> WiC-TSV has <strong>three subtasks</strong> - participants can submit results in any of the subtasks:</p> <p>Subtask 1: Definitions</p> <p>In Subtask 1 systems make use of <strong>definitions</strong> for deciding whether the target word in context corresponds to the given definition or not.</p> <p>Subtask 2: Hypernyms</p> <p>In Subtask 2 systems make use of <strong>hypernymy</strong> information for deciding whether the target word in context is a hyponym of the given hypernym or not.</p> <p>Subtask 3: Definitions + Hypernyms</p> <p>In subtask 3 systems can make use of <strong>both</strong> sources of information, i.e., definitions and hypernyms.</p>
More precise tracking of horizontal than vertical target motion with both the eyes and hand
<p>Those files contain individual data from a large cohort of participant (N=62). </p> <p>In the excel file (DATAmain), each sheet presents one set of variables (with individual value for each trial).</p> <p>This file contains information regarding eye and hand tracking performance (distance+lags), as well as smooth pursuit gains. </p> <p>The other files contain data that we used for the detailed analysis of saccades and lags, as well as the scripts that can be run with Perl. One script is for analysing the lag (Danion.pl) and the other one for analysing the saccades (saccades.pl). The other files (.txt and .dat) that were used for these analyses. Note that some library is needed (common_subroutines, draw_figure, and for the anova’s routines_that_use_R), meaning that you need to have R installed. </p> <pre>Regarding data acquisition we employed a program called Docometre that can be uploaded at the following address: http://139.124.68.1/buloup/index.php?selectedMenu=DOCoMETRe&lang=_fr When this program is installed, it needs to be run with BaselineTracking.dcm We also provide .BAS and .T91 files that correspond to the compiled version of each pattern Regarding visual stimuli, another program called ICE needs to be installed on a separate computer that receives information (target+cursor) from docometer, it can be uploaded at : https://trello.com/b/EtNCNrZH/icehttps://trello.com/b/EtNCNrZH/ice ICE needs to be run with Visuomotor.ice Visuomotor.icepro Visuomotor.txt and Visuomotor.icemat in the respective folder (icepro in Protocol folder, icemat and ice in Scenario Folder, and txt in Serie folder) Note that both Docometre and ICE need to be run with similar equipement as our (including Adwin Gold systems, Megatron joystick, video screen, graphic cards, and desktop eyelink providing analog signals to docometre). Adequate numbering of analogic channels needs also to be ensured. </pre>
Human Stromal Antigen 1 (STAG1) Cohesin Subunit SA-1; A Target Enabling Package
<p>Loss of function mutations in the cohesin subunit gene <a href="https://www.ncbi.nlm.nih.gov/gene/10735">STAG2</a> are common in a variety of cancers (1). These cells become dependent on the paralogous cohesin subunit <a href="https://www.ncbi.nlm.nih.gov/gene/10274">STAG1</a> (2-4). Mutants of STAG1 that disrupt the binding to the cohesin subunit <a href="https://www.ncbi.nlm.nih.gov/gene/5885">RAD21</a> cannot complement the loss of STAG2. This TEP examines the druggability of STAG1 as a synthetic lethal strategy to treat <em>stag2<sup>-</sup></em> cancers. The TEP includes crystal structures of two domains of STAG1, alone and in complex with Rad21-rderived peptides. We performed screens of a fragment library and identified small molecules bound to pockets in the two domains of STAG1. We also developed assays for binding of RAD21 peptides to STAG1, which can be used to screen for molecules that disrupt binding.</p>
Human Pleckstrin Homology domain Interacting Protein (PHIP); A Target Enabling Package
<p>SGC Oxford has expressed, purified and crystallized the second bromodomain of PHIP as part of the probe programme. Fragment screening and X-ray crystallography identified binders, some of which optimised to uM affinity. However, molecules with probe properties were not obtained. Consequently it has been decided to put the information generated into the public domain.</p>
Human With No Lysine Kinase 3 (WNK3); A Target Enabling Package
<p>Kinases WNK1-4 regulate cation-chloride cotransporters via phosphorylation of SPAK and OSR1 and thereby control salt homeostasis, cell volume and blood pressure. Gain of function mutations in WNK kinases are found in Gordon’s hypertension syndrome suggesting the WNK pathway as a therapeutic target. WNK3 inhibition in particular has also been shown to reduce cerebral injury after Ischemic stroke. Here we present assays and crystal structures that define (i) the molecular basis for disease mutations; (ii) the multiple functional domains of WNK kinases and their protein interactions; (iii) the binding of small molecule kinase inhibitors and a potential allosteric pocket.</p>
Human Hydroxyacid Oxidase (HAO1); A Target Enabling Package
<p>This project provides the tools and data to develop small molecule inhibitors for an inherited metabolic disorder (Primary hyperoxaluria type 1) due to the defective enzyme (<a href="https://www.ncbi.nlm.nih.gov/gene/189">AGXT</a>), by targeting the enzyme (<a href="https://www.ncbi.nlm.nih.gov/gene/54363">HAO1</a>) upstream of the glyoxylate metabolic pathway to mitigate the defect (i.e. substrate reduction approach). This TEP package includes recombinant human HAO1 purification protocols, structures of the HAO1 in different states, <em>in vitro </em>assays to detect ligand/inhibitor binding (DSF, SPR) and enzyme activity (amplex red assay) of human HAO1, as well as initial chemical matters identified from crystallography-based fragment screening.</p>
Human Methylene- tetrahydrofolate reductase (MTHFR) A Target Enabling Package (TEP)
<p>The folate and methionine cycles are essential metabolic pathways for life, involved respectively in DNA synthesis and generation of the ubiquitous methyl donor S-adenosylmethionine (SAM). The enzyme 5,10-methylenetetrahydrofolate reductase (<a href="https://www.ncbi.nlm.nih.gov/gene/4524">MTHFR</a>) represents a key regulatory connection between these cycles, hence exerting a strong influence on an array of diseases. This TEP presents the first structures for any eukaryotic MTHFR, revealing a novel SAM-binding fold. The TEP provides additional mass spectrometry, activity assay and biophysical binding methods yielding mechanistic insights into how phosphorylation and allosteric binding of SAM act in concert to inhibit MTHFR activity. This work further provides the starting point for the design of tool molecules (e.g. SAM-analogues) aimed at disrupting the SAM-induced inhibition of MTHFR activity.</p> <p> </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.