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1,923 results for “compounds”
Year-round observations of stable carbon isotopic composition of diacids and related compounds in fine aerosols at Tianjin, North China – Data set
<p>To better understand the origins and photochemical processing of water-soluble organic aerosols in the Tianjin region, North China, we studied the stable isotopic composition (δ<sup>13</sup>C) of diacids, oxoacids, α-dicarbonyls, citric acid and fatty acids in fine aerosols (PM<sub>2.5</sub>) collected at an urban (Nankai District, ND; <em>n</em> = 121) and a suburban (Haihe Education Park, HEP; <em>n</em> = 40) sites in Tianjin from 5 July 2018 to 4 July 2019. The δ<sup>13</sup>C of diacids and related compounds were measured using a capillary gas chromatography (Agilent 7890B) coupled with isotope ratio mass spectrometry (GC-irMS) system. Based on seasonal variations in δ<sup>13</sup>C of selected species and linear relations with their concentrations and mass ratios, we found that the diacids and related compounds were mainly derived from fossil fuel including coal combustion and biomass burning and photochemical processing, preferably in gaseous- and aqueous-phases in warm (March-September) and cold (October-February) periods, respectively, in Tianjin, North China.</p>
A mechanism for the strange metal phase in rare-earth intermetallic compounds
<p>Codes and numerical data for each Figure created for the study in Jiangfan Wang, et al., <em>A mechanism for the strange metal phase in rare-earth inter-metallic compounds </em>and its supporting information.</p>
Blood Exposome Database Compounds with DDA spectra coverage
<p>The last two columns in the CSV file has 1) DDA spectra (publicly available) count for blood exposome database compound list and 2) coverage (y/n) in the NIST 2020 database. First block of the InchiKey was used to query the spectral data that was downloaded from the MONA, GNPS, MS-DIAL repositories. </p> <p>It can be useful for prioritizing compounds that need to be purchased for new DDA data collection, or they can be candidates for in-silico fragmentation analyses. </p>
Dataset from paper "Dynamic Concentration Factor: A Novel Parameter For The Rigorous Evaluation Of Solar Compound Parabolic Collectors"
<ul> <li>Dynamic Concentration Factor as a function of the beam angle (α) for CPC with different acceptance angles (θ), reflectivity (r) of the collector surface ranging from 0.0 to 1.0, and optical density ranging from 0.0 to 10.0</li> <li>Diffuse Dynamic Concentration factor for CPC with different acceptance angles (θ), reflectivity (r) of the collector surface ranging from 0.0 to 1.0, and optical density ranging from 0.0 to 10.0</li> <li>Experimental validation of the Dynamic Concentration Factor using actinometry results</li> <li>Independence test of Dynamic Concentration results of the number of rays cast in the software tool.</li> <li>Full-precision data of the Dynamic Concentration Factor as a function of the beam angle (α) for CPC with different acceptance angles (θ), reflectivity (r) of the collector surface ranging from 0.0 to 1.0, and optical density ranging from 0.0 to 10.0</li> </ul>
Nanotubes from the Misfit Layered Compound (SmS)1.19TaS2: Atomic Structure, Charge Transfer, and Electrical Properties_experimental dataset
<p>This dataset contains the raw experimental data for the Sreedhara et al., Nanotubes from the Misfit Layered Compound (SmS)1.19TaS2: Atomic Structure, Charge Transfer, and Electrical Properties, <em>Chem. Mater.</em> 2022, 34, 4, 1838–1853</p>
Compound activity data sets for 15 biological targets compiled from the ChEMBL and PubChem databases.
<p>Compound activity data sets for the 15 biological targets are deposited, along with structure-activity relationship matrices IDs. Active compounds were extracted from the ChEMBL database and inactive were from the PubChem database. Details of the data sets are described in the original publication. and the summary of the data sets is given in the readme.txt file. </p>
Relative binding free energy between chemically distant compounds using a bidirectional non-equilibrium approach
<p>Data from "Relative binding free energy between chemically distant compounds using a bidirectional nonequilibrium approach"</p> <p>Submitted to J Chem Theory Comput, February 2022.</p> <p>This archive contains the following directories:</p> <p><br> traj -> This directory contains trajectory files for SAMPL9:</p> <p> g??_w.pdb.gz file contains ~ 160 snapshots from the 48 ns HREM sampling<br> of the target bound state of G1-G13 including water solvent.</p> <p> g??_1.pdb.gz file contains ~ 3500 snapshots (no solvent included) of the<br> target bound state of G1-G13</p> <p><br> work -> This trajectory contains the work data (in kJ/mol) obtained in<br> the NE trajectories for SAMPL9:</p> <p> gxx-gyy_b_TIME.wrk is the work sample obtained for the xx->yy transmutation<br> in the bound state with a duration time of TIME.</p> <p> gxx-gyy_u_TIME.wrk is the work sample obtained for the xx->yy transmutation<br> in the unbound state with a duration time of TIME.</p> <p>pdb -> This directory contains the pdb initial structures of the G1-G18 guests and the WP6 host</p> <p>ff -> This directory contains the force field specification for SAMPL9:</p> <p> the PrimaDORAC generated (http://www1.chim.unifi.it/orac/primadorac/)<br> tpg and prm files for the guests and the host in orac format. (see<br> http://ftp.chim.unifi.it/orac/MAN/orac-manual.html)</p> <p>bin -> This directory contains the script files to compute all bidirectional and unidirectional RBFE estimates as reported in Table 2 of the paper.<br> In order to compute an RBFE using the work data in the work dir, do the following:<br> 1) cd into the bin directory<br> 2) issue the command<br> source source_this_file.bash<br> (N.B.: gfortran must be installed)<br> 3) cd ../<br> 4) from the main dir, issue the command:<br> RBFE.bash -b 720 -u 360 B A<br> where B and A are the ghost and physical compound, respectively<br> Results for DG(A->B) are printed to the standard output</p> <p> Example: <br> RBFE.bash -b 720 -u 360 g01 g03 > g03g01<br> In the g03g01 file, estimates and properties of the work data are<br> printed in the format<br> "g05->g02 DG_bar= -5.13 0.37 DG_ff_G= -4.2 0.8 DG_ff_J= -3.0 0.4 sig_AB_u= 0.90 sig_AB_b= 2.16 ADT_AB_u= 0.26 ADT_AB_b= 0.23 DG_rr_G= 130.5 33.5 DG_rr_J= -7.2 0.8 sig_BA_u= 1.10 sig_BA_b= 13.61 ADT_BA_u= 0.48 ADT_BA_b= 3.40 DG_fr_G= -4.27 1.04 DG_fr_J= -3.23 0.58 bias_fr= 0.2 DG_rf_G= 127.88 30.30 DG_rf_J= -7.16 0.66 bias_rf= 0.0 DG_BAR= -5.26 0.0 tb= 720 tu= 360"</p> <p> To compute all DDG estimates of Table 2 launch the script<br> "do_all.bash" from the main dir </p> <p>shift-pot -> This directory contains two gnuplot scripts showing the evolution of the<br> Beutler LJ and elec soft-core potentials (soft.gplt) and of the shifted LJ and<br> elec soft-core potentials used in this work (shift.gplt)<br> </p>
Pre-Analysis Bioinformatics Files for The Microbiome and Volatile Organic Compounds Reflect the State of Decomposition in an Indoor Environment
<p>Data statistics before and after trimming, FastQC reports before and after trimming, MultiQC reports before and after trimming, commands for the Kraken2-Bracken analysis, and classification reports. Read the read.me file for file names and descriptions. </p>
Bulk components and diacids and related compounds in size-segregated aerosols at Tianjin, North China – Data set
<p>To better understand the sources of atmospheric aerosols in winter, we collected size-resolved (9-stage) aerosols at Tianjin, North China, and studied for inorganic ions, carbonaceous components, diacids and related compounds. Inorganic ions were measured using ion chromatography (ICS-5000 System, China, Dai An). Organic carbon (OC) and elemental carbon (EC) were measured using OC/EC analyzer (USA, Sunset Laboratory Inc.), based on thermal light reflectance following the IMPROVE protocol of the protective visual environment. Water-soluble organic carbon (WSOC) was measured using the total organic carbon (TOC) analyzer (model: OI, 1030W + 1088). Concentrations of diacids and related compounds were measured using a capillary gas chromatography (GC; Agilent 7890B). Peak identification was carried out with reference to authentic standards retention time measured by GC-FID and mass spectra performed using a GC-mass spectrometry (GC-MS) system. Based on the results obtained, we found that the atmospheric aerosols over the Tianjin region, North China were derived from mixed: both anthropogenic and biogenic, sources and the subsequent secondary formation/transformations were also important in winter.</p>
Compound Information in the EBI Metabolights Repository
<p>Compound files from all studies in the EBI Metabolights database were stacked together. It has ~50K unique chemical names. </p>
Supplemental data and code for Climate change will amplify the inequitable exposure to compound heatwave and ozone pollution
<p>Supplemental data and code for Climate change will amplify the inequitable exposure to compound heatwave and ozone pollution</p>
Annotated compounds in extracts from alpine aromatic and medicinal plants grown in an aeroponics system
<p>The compounds were annotated by comparing the experimental HRMS/MS spectra of the samples with an <em>in silico</em> MS/MS spectral database of natural products.</p>
DE BAY IRENE COMPOUND FLOODING USING DHSVM-FVCOM
<p>Data sets used in DHSVM and FVCOM model development and validation, and result analysis.</p>
Predicting compound-protein interaction using hierarchical graph convolutional networks
<p>This repository contains the datasets which are used in the article "Predicting Compound-Protein Interaction using Hierarchical Graph Convolutional Networks".</p>
Curated data-set of crystal-structure prototypes of binary and ternary sp-d valent compounds
<p>Curated collection of binary and ternary compounds of sp-valent elements and d-valent elements and their crystal-structure prototype. The data set includes binary and pseudo-binary compounds in binary prototypes (BinaryPrototype-BinaryCompound.csv), offstoichoimetric and ternary compounds in binary prototypes (BinaryPrototype-BinaryOffstoichiometricAndTernaryCompound.csv) and ternary compounds in ternary prototypes (TernaryPrototype-TernaryCompound.csv). The first column in each data set corresponds to the crystal-structure prototype, the second column to the chemical composition. Ternary compositions labelled A-B+C indicate that element B and element C occupy the same sublattice of the crystal structure. A+B-C correspondingly indicates that element A and element B occupy the same sublattice. These data sets were used to construct structure maps for predicting the crystal structure of a compound from only its chemical composition. For details on curation, further discussions and structure maps see original publications (Chem. Mater. 28, 2550−2556, 2016 and Modelling Simul. Mater. Sci. Eng. 25, 074002, 2017).</p>
Results for blind docking Tocriscreen 2.0 compounds against AlphaFold2 structural modules of human and parasite proteins
<p>Docking (GNINA 1.0) of 1280 Tocriscreen 2.0 compounds against >4000 AlphaFold structures from humans and the parasitic nematode <em>Brugia malayi</em>. </p> <p>Results are provided as Pickle objects or GZipped CSVs.</p> <p>Tuned machine learning models (random forest and XGBoost) are also included for classifying actives/decoys.</p>
Circum-Arctic distribution of chemical anti-herbivore compounds arctic shrubs
Spatial variation in plant chemical defence towards herbivores can help us understand variation in herbivore top-down control of shrubs in the Arctic and possibly also shrub responses to global warming. Less defended, non-resinous shrubs could be more influenced by herbivores than more defended, resinous shrubs. However, sparse field measurements limit our current understanding of how much of the circum-Arctic variation in defence compounds is explained by taxa or defence functional groups (resinous/non-resinous). We measured circum-Arctic chemical defence and leaf digestibility in resinous (Betula glandulosa, B. nana ssp. exilis) and non-resinous (B. nana ssp. nana, B. pumila) shrub birches to see how it varies among and within taxa and functional groups. Using LC-MS metabolomic analyses and in-vitro leaf digestibility via incubation in cattle rumen fluid, we analysed defence composition and leaf digestibility in 128 samples from 44 tundra locations. We found biogeographical patterns in anti-herbivore defence where mean leaf triterpene concentrations and twig resin gland density were greater in resinous taxa and mean concentrations of condensing tannins were greater in non-resinous taxa. This indicates a biome-wide trade-off between triterpene or tannin dominated defences. However, we also found variations in chemical defence composition and resin gland density both within and among functional groups (resinous/non-resinous) and taxa, suggesting these categorisations only partly predict chemical herbivore defence. Complex tannins were the only defence compounds negatively related to In-Vitro Digestibility, identifying this previously neglected tannin group as having a potential key role in birch anti-herbivore defence. We conclude that circum-Arctic variation in birch anti-herbivore defence can be partly derived from biogeographical distributions of birch taxa, although our detailed mapping of plant defence provides more information on this variation and can be used for better predictions of herbivore effects on arctic vegetation.
Volatile organic compounds (VOIs) in seawater and sediment pore water collected in Funka Bay and Bering and Chukchi Seas
<p>The data of volatile organic compounds (VOIs) in seawater and sediment pore water collected in the Funka Bay, Hokkaido, Japan, and the Bering and Chukchi Seas. Funka Bay's samples were collected in 2018-2019. Bering and Chukchi Seas' samples were collected in July of 2017 and 2018. The article entitled "Marine sediment as a likely source of methyl and ethyl iodides in subpolar and polar seas" by Ooki et al. published by Communications Earth & Environment used these datasets. The datasets are also provided as supplementary data1-4 in the article. Details of datasets are described in the article. Please cite this article when you use these datasets.</p>
Invasive plant species that experience lower herbivory pressure may evolve lower diversities of chemical defence compounds in the exotic range
<p><strong>ABSTRACT</strong></p> <p><strong>PREMISE</strong></p> <p>Invasive plant species often escape from specialist herbivore species and are likely to experience herbivory mostly from generalist herbivore species in the exotic range. Consequently, the Shifting Defence Hypothesis (SDH) predicts that invasive plants will express higher concentrations of qualitative defence compounds to deter dominant generalist herbivores in the exotic range. Here, I additionally propose a Reduced Chemical Diversity Hypothesis (RCDH), which predicts that reduced herbivory pressure will select for invasive plant genotypes that produce lower diversities of defence compounds in the exotic range.</p> <p><strong><span>METHODS</span></strong></p> <p>I tested whether: (1) Invasive <em>Brassica nigra</em> populations express a lower diversity and an overall higher concentration of glucosinolate compounds than native-range <em>B. nigra</em>; (2) <em>Brassica nigra</em> individuals that express high diversities and concentrations of glucosinolates are more attractive to specialist and deterrent to generalist herbivores; (3) Tissues of invasive <em>B. nigra </em>are less palatable to two generalist herbivores <em>Theba pisana</em> and <em>Helix aspersa</em> than tissues of native-range<em> B. nigra</em>.</p> <p><strong><span>RESULTS</span></strong></p> <p>Invasive <em>B. nigra </em>populations expressed a significantly lower diversity of glucosinolate compounds and a marginally higher concentration of total glucosinolate compounds. Leaf tissues of the invasive <em>B. nigra</em> were significantly less palatable to <em>T. pisana</em> and marginally less so to <em>H. aspersa</em>. <em>Brassica nigra</em> individuals that expressed high concentrations of total glucosinolate compounds were visited by a low diversity of generalist herbivore species in the field.</p> <p><strong><span>CONCLUSIONS</span></strong></p> <p>The biogeographical differences in glucosinolate profiles of invasive and native-range populations of <em>B. nigra</em> may be the result of differential herbivore selection pressures in the respective ranges.</p>
PubChem Compounds with MeSH Annotations
<p>PubChem database was searched for compounds that had a MeSH annotation. It is great that PubChem now allows a direct download for these compounds in a rich CSV file. </p>
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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.
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.