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34 results for “NMR raw data”
Raw NMR FID data of cryptoporic acid derivatives isolated from Cryptoporus volvatus fruiting bodies
<p>This is a NMR FID data of cryptoporic acid derivatives isolated from fruiting bodies of <em>Cryptoporus volvatus</em> (Polyporaceae).</p> <p>Isolation and structural elucidation of these compounds will be reported in the article titled "Species prioritization based on spectral dissimilarity: A case study of polyporoid fungi species", which is currently under revision.</p>
Raw data for "Modular Pulse Program Generation for NMR Supersequences"
<p>Raw data for the paper <em>Modular Pulse Program Generation for NMR Supersequences</em>, which accompanies the GENESIS website for automatic generation of NOAH pulse programmes.</p> <p>Please note that this contains data only, not any of the accompanying figures. The same datasets may alternatively be downloaded from GitHub, if preferred: https://github.com/yongrenjie/genesis-paper/releases/tag/final-revision</p> <ul> <li>For the figures, and the scripts used to generate them, please see https://github.com/yongrenjie/genesis-paper (the repository readme contains detailed instructions on reproducing the figures)</li> <li>For the GENESIS source code and a LaTeX version of the paper itself, please see https://github.com/yongrenjie/genesis</li> <li>For the GENESIS website itself, please see https://nmr-genesis.co.uk</li> </ul>
Enantioselective Assembly of Congested Cyclopropanes using Redox-Active Aryldiazoacetates - NMR, HRMS and X-ray Raw Data
<p>NMR, HRMS and single crystal X-ray diffraction raw data for the compounds in the manuscript ACS Catalysis 2019, DOI: <a href="https://doi.org/10.1021/acscatal.9b02615">https://doi.org/10.1021/acscatal.9b02615</a></p>
Raw data used in the manuscript titled "Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using 1H HR MAS NMR Spectroscopy "
<p>The folder contains raw data used in the manuscript titled "Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer Using <sup>1</sup>H HR MAS NMR Spectroscopy ".</p> <p> </p> <p> Raw data measured on Bruker Avance III 400 MHz NMR spectrometer:</p> <p>- 1D <sup>1</sup>H HR MAS NMR spectra (path: <em>Patient_code – Sample_code/500/fid</em>)</p> <p>- 2D <sup>1</sup>H-<sup>1</sup>H J-resolved HR MAS NMR spectra (path: <em>Patient_code – Sample_code/600/ser</em>).</p> <p> </p> <p>Metadata is included in <em>Metadata.xlsx</em> file.</p> <p>Each sample is described with the following parameters:</p> <p>- patient code (after anonymization),</p> <p>- sample code (the label <em>l</em> or <em>r</em> denotes the <em>left</em> or <em>right</em> ovary in patients from whom samples were obtained bilaterally),</p> <p>- sample weight,</p> <p>- clinic-pathological parameters (such as: age, BMI, menopausal status, diagnosis, FIGO stage),</p> <p>- percentage tissue content obtained from histopathological analysis after HR MAS NMR studies (cancer cells, epithelial compartment within benign tumors, necrosis, inflammation, fibrosis, calcification, normal ovary, vessels, fatty tissue).</p> <p> </p> <p>Some samples were considered representative of particular tissue components:</p> <p>- cancer (HGSOC) compartment,</p> <p>- fibrotic stroma within malignant (HGSOC) tumors,</p> <p>- fibrotic stroma within benign tumors,</p> <p>- normal ovary tissue (the samples collected from the control group),</p> <p>- normal ovary tissue (the samples collected from the cancer patients),</p> <p>- necrosis,</p> <p>- non-tumoral fibrous tissue / fibrous tumor capsule (obtained from the patients with benign non-neoplastic lesions)</p> <p>- corpus albicans</p> <p>The assignment of the samples to these categories is indicated in the column <em>Tissue components.</em></p> <p><em> </em></p> <p>The samples classified as outliers in PCA model 1 are indicated in the column <em>Outliers</em>.</p> <p>The samples included in multivariate models are indicted in the columns: <em>PCA 2, PCA 3, PCA 4, PCA 5, PCA 5a, PCA 6, OPLS-DA 1, OPLS-DA 2, OPLS-DA 3, OPLS-DA 4, OPLS-DA 5, OPLS-DA 6 and OPLSR.</em></p> <p><em> </em></p>
Raw data and figures for "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules"
<p>Datasets, pulse programmes, processing scripts, and figures for the publication "Increasing Sensitivity and Versatility in NMR Supersequences with New HSQC-based Modules" (J. Magn. Reson., accepted, 2021).</p> <p>Please see the README.txt file for more information.</p> <p>If you are only interested in pulse programmes and processing scripts, then this dataset will likely be too big for your liking (it is ca. 9 GB because there is a lot of 2D data). You can download the pulse programmes and processing scripts from the Bruker User Library https://www.bruker.com/en/services/bruker-user-library.html.</p> <p><strong>Changelog</strong></p> <p>v1.0.1: some quality of life improvements to the Python NUS script to stop it from being accidentally used on old pulse programmes.</p> <p>v1.0.2: fixed a bug in the v1.0.1 Python script. It now also resets FnTYPE in case the user has changed it.</p>
MATLAB scripts and raw experimental data for the paper "Optimizing measurements of linear changes of NMR signal parameters" by Javier Agustin Romero, Krzysztof Kazimierczuk and Paweł Kasprzak
<p>Classical_fit.m - Comparison of simulation results and theoretical predictions for the linear fit of the resonance frequencies. </p> <p>Radon_transform - the same, but using Radon transform to determine linear coefficients.</p> <p>Amplitude.m - Comparison of errors of the linear coefficients for varying amplitude fit in simulations and theory.</p> <p>process_measurements.m - script to process experimental data (caffeine peak at 7.90 ppm). The data are stored in real.mat and imag.mat</p> <p>For the details of theoretical formulas, see the paper "Optimizing measurements of linear changes of NMR signal parameters" by Javier Agustin Romero, Krzysztof Kazimierczuk, and Paweł Kasprzak. The scripts were used to generate Figures in the paper.</p>
Raw NMR FID data of sesquiterpenes from co-culture of Phellinus orientoasiaticus and Xylodon flaviporus
<p>This is a NMR FID data of sesquiterpenoids isolated from co-culture of Phellinus orientoasiaticus and Xylodon flaviporus.</p> <p>Isolation and structural elucidation of these compounds will be reported in the article titled "Cyclohumulanoid Sesquiterpenes Induced by the Non-competitive Co-culture of Two Basidiomycetous Fungi, <em>Phellinus orientoasiaticus</em> and <em>Xylodon flaviporus</em>", which is currently under review.</p>
NMR assignment of methyl groups in solid-state using 1H-detection and fast MAS - NMR raw and processed data
<p>This data set contains raw NMR data in Bruker format for experimental series on (1) 2,3-13C-labelled microcrystalline alanine, (2) U-13C,15N-labelled N-fomylated microcrystalline tripeptide Met-Leu-Phe, and (3,4) two differently labelled (ILV-C4 and ILV-C5) microcrystalline chicken-alpha-spectrin SH3 domain. Measurements were performed at 14.4 T and 55.5 kHz MAS (alanine), 18.8 T and 55.5 and 98 kHz MAS (fMLF), 23.5 T and 55.5 kHz (SH3 C5), 18.8T and 55.5 and 94.5 kHz MAS (SH3 C5) and 18.8T and 55.5 and 94.5 kHz MAS (SH3 C4). The data set also contains Fourier processed data (spectra) in UCSF format, Sparky project, save and peak list files. Pulse programs for Bruker spectrometers are provided. The data set is complemented with SIMPSON scripts for simulation of spin dynamics under aformentioned conditions.</p>
Raw data for 'Analysing binding stoichiometries in NMR titration experiments using Monte Carlo simulation and resampling techniques'
<p>Repository of the raw data and SupraFit binaries (for Windows, Linux and macOS) for the research article:</p> <p><strong>Analysing binding stoichiometries in NMR titration experiments using Monte<br> Carlo simulation and resampling techniques</strong></p> <p> </p> <p>It contains the SupraFit nigthly builds 2.5.98 for Windows (<em>SupraFit-nightly-2.5.98-x86_x64-Windows.zip</em>), Linux (<em>SupraFit-nightly-2.5.98-x86_64-Linux.tar.gz</em>) and macOS (<em>SupraFit-nightly-2.5.98-macOS.dmg</em>).</p> <ul> <li> <p><em>Simulated Experiments.suprafit</em> contains the simulated experimental data</p> </li> <li> <p><em>Simulated 1_1 Experiment.suprafit</em> contains the raw data of the 1:1 data set after several statistical post-processing analyses were performed</p> </li> <li> <p><em>Simulated 1_1_1_2 Experiment.suprafit</em> contains the raw data of the 1:1/1:2 data set after several statistical post-processing analyses were performed</p> </li> <li> <p><em>Simulated 2_1_1_1 Experiment.suprafit </em>contains the raw data of the 2:1/1:1 data set after several statistical post-processing analyses were performed</p> </li> <li> <p><em>Simulated 2_1_1_1_1_2 Experiment.suprafit </em>contains the raw data of the 2:1/1:1/1:2 data set after several statistical post-processing analyses were performed</p> </li> <li> <p><em>MC-simulation 1_1_1_2 Experiment.suprafit </em>contains the raw data for Figure 4 in the article</p> </li> </ul>
NMR_raw_data for "Native Metabolomics Identifies the Rivulariapeptolide Family of Protease Inhibitors"
<p>Raw 1D/2D NMR data and chemical structures for compounds <strong>1 </strong>- <strong>6</strong> of the study "Native Metabolomics Identifies the Rivulariapeptolide Family of Protease Inhibitors".</p>
Raw NMR data for two constructs of the 8-17 DNAzyme in presence of diferent metal ion cofactors.
<p>The provided NMR dataset contains mainly spectra collected for a unimolecular 8-17 DNAzyme construct, featuring shortened substrate-binding arms: 5'-CGC CGG GGT CGA AGA CTG CCA GCG GCT CGA CGG CG-3' (labelled 8-17 short or GTC within the dataset). The spectra are provided for a number of different experimantal conditions:</p> <p>1) in the presence of both Zn2+ and Na+ (conditions used for structure determination)</p> <p>2) in the presence of Zn2+</p> <p>3) in the presence of Na+</p> <p>4) in the presence of Mg2+</p> <p>5) in the presence of Pb2+</p> <p>6) in the presence of both Zn2+ and Na+(Zn2+ titration to a sample initially containing only Na+)</p> <p>In addition 1H NMR titrations were also recorded for the 8-17 DNAzyme construct, used in the previous crystallographic study (labeled 'crystalo' within the dataset). Titrations using Zn2+, Na+, Mg2+ an Pb2+ are provided.</p>
NMR Raw data and HRMS data of products
<p>NMR raw data and HRMS spectra of products in the publication of "Stereoselective conjugate cyanation of enals by combining photoredox and organocatalysis" in Nature Catalysis, Volume 6, pages 332-338 (2023).</p> <p> </p>
Reductive synthesis of azoxypyridines from nitropyridines using hydroxides in alcoholic media by L. Caruana et al. - Raw NMR data
<p>NMR raw data for the work "Reductive synthesis of azoxypyridines from nitropyridine using hydroxides in alcoholic media"</p>
Pure Isotropic Proton Solid State NMR raw data
<p>This dataset contains all raw NMR data (in Topspin and JCAMP format) together with the MATLAB scripts used in the JACS publication named: "Pure Isotropic Proton Solid State NMR" (DOI: 10.1021/jacs.1c03315 )</p>
Raw data for NMR-POISE: On-the-fly, Sample-tailored Optimisation of NMR Experiments
<p>The NMR-POISE paper can be found at: <em>Anal. Chem.</em> <strong>2021,</strong> <em>93</em> (31), 10735–10739 (DOI: <a href="https://doi.org/10.1021/acs.analchem.1c01767">10.1021/acs.analchem.1c01767</a>).</p> <p>The majority of one- and multi-dimensional NMR experiments, indispensable to chemists in many areas of research, are often run with generic or "compromise" parameter values that are not optimised. This is particularly problematic when robust, automated acquisition on a variety of samples is desired. Here we present a Python package, NMR-POISE (Parameter Optimisation by Iterative Spectral Evaluation), with full integration into Bruker’s TopSpin software, that utilises feedback control for on-the-fly, sample-tailored optimisation of NMR experiments. POISE provides a highly extensible and user-friendly framework which allows its core optimisation algorithms to be implemented in a wide variety of scenarios.</p> <p>The data attached herein provide examples of optimisation procedures where POISE can be used to great effect. The raw NMR data is attached here, together with all of the scripts used for processing and plotting this data (which can be used to directly regenerate the figures in the manuscript).</p> <p>The raw NMR data is in the "datasets" directory, and the processing scripts in the "figures" directory. The scripts can be run as long as this directory structure is maintained, but require v0.4.1 of the "penguins" Python package: this can be installed using the command "pip install penguins=0.4.1" (without quotes). Please refer to the Supporting Information of the POISE paper for more details, including a full description of the individual datasets.</p> <p><strong>Changelog</strong></p> <p>v1.1.0 of this dataset contains extra raw data and figures added during revision of the manuscript.</p>
Raw data and scripts for "Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes" by Shchukina et al.
<p>A series of 15N HSQC spectra of aSyn at temperatures 15,17..43C acquired with and without the addition of POPG-based liposomes. The spectra can be processed with sparse undersampling at various levels (scripts are provided).</p>
Raw Data From: "Investigating the crystallinity of hard candies prepared and stored at different temperatures with low field-NMR relaxometry"
<p><strong>Background: </strong>In this study, hard candies were produced by using sucrose, glucose syrup and water. They were cooked at different temperatures, changing from 135 to 145 °C with an interval of 2.5 °C. They were stored at different storage temperatures, which were 25, 4, -18 and -80 °C. Hard candies placed at room temperature were stored for 2 months. In order to understand the crystallization characteristics of the hard candies, time domain (TD) proton nuclear magnetic resonance (<sup>1</sup>H-NMR) parameters of longitudinal relaxation time (T<sub>1</sub>) and second moment (M<sub>2</sub>) measurements were conducted. Moisture contents of the hard candies were determined by Karl-Fischer titration. X-ray diffraction experiments were also conducted as the complementary analysis.</p> <p><strong>Results: </strong>Increasing cooking temperature increased the crystallinity and decreased the moisture content of the hard candies significantly (P ≤0.05). Furthermore, storage temperature and storage time had significant effects on the crystallinity of the hard candies (P ≤0.05). The results of T<sub>1</sub> and M<sub>2</sub> correlated with each other (r > 0.8, P ≤ 0.5) and both produced the highest value at the cooking temperature of 145 °C and storage temperature of 4 °C (P ≤ 0.05). The values of T<sub>1</sub> and M<sub>2</sub> were obtained as 245.9 ms and 13.0 × 10<sup>-8</sup> Hz<sup>2</sup>, respectively, for the cooking temperature of 145 °C and storage temperature of 4 °C.</p> <p><strong>Conclusion: </strong>This study demonstrated that the crystallinity of hard candies can be observed and examined by TD-NMR relaxometry, as an alternative to commonly used methods. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.</p>
NMR raw data for: DTX3L ubiquitin ligase ubiquitinates single-stranded nucleic acids
Open the record for dataset details and reuse information.
Direct Decarboxylation of Trifluoroacetates Enabled by Iron Photocatalysis – NMR raw data
<div> <p>NMR raw data and HRMS of the compounds in the publication cited.</p> </div>
Raw NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis
<p>This is NMR FID data of biotransformed phenolic xyloside by Lentinus brumalis.</p> <p>Isolation and structural elucidation of these compounds will be reported in the article titled "Uncovering detoxification enzymes diversity of wood-decaying fungi through qualitative untargeted metabolomics", which will be submitted soon.</p>
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