Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
535
datasets available to search
ShareScore release 0.9.0
Dataset results
535 results for “NMR,”
Paramagnetic tailored experiments for the NMR investigation of reduced and oxidized [2Fe-2S]-mitoNEET
<p>We report here the complete data sets and the pulse programs for the NMR spectra of the human iron sulfur binding protein mitoNEET, in its oxidized and reduced states. These data have been used in the publication “The long-standing relationship between Paramagnetic NMR and Iron-Sulfur proteins: the mitoNEET example. An old method for new stories or the other way around?”. This folder includes: paramagnetic 1D proton NOE experiments, <sup>15</sup>N-IR-HSQC-AP experiments and CON <sup>13</sup>C direct detection experiments in their diamagnetic and paramagnetic version. All these data have been used to identify NMR signals of residues surrounding the metal cofactor. Along with the raw data we report also the pulse programs of the paramagnetic tailored experiments. The NMR spectra of both oxidation states of mitoNEET are significantly different from those reported for previously investigated [Fe<sub>2</sub>S<sub>2</sub>]<sup>2+/+</sup> proteins and provide a detailed description of the unique electronic properties of mitoNEET, that is essential for the understanding of its the biological function.</p>
Megalocarpoidolide_I NMR data
<p>Megalocarpoidolide_I, raw and processed NMR data; LSD (Logic for Structure Determination) software input file and result.</p>
Simulation trajectories for the article "Molecular conformation and bilayer pores in a nonionic surfactant lamellar phase studies with 13C-1H solid-state NMR and molecular dynamics simulations"
<p>Simulation trajectories for the article "Molecular conformation and bilayer pores in a nonionic surfactant lamellar phase studies with 1H-13C solid-state NMR and molecular dynamics simulations" Langmuir 2014, 30 (2), pp 461–469 http://dx.doi.org/10.1021/la404684r</p> <p>System: 80 wt% C12E5, T=298K</p> <p>Other files available: http://dx.doi.org/10.6084/m9.figshare.861071</p>
Primary NMR Data Supporting the Article "Synthetic approach to 2-alkyl-4-quinolones and 2-alkyl-4-quinolone-3-carboxamides based on common β-keto amide precursors"
<p>This archive contains raw 1H/13C FIDs and associated data in Bruker-specific format that can be viewed with Bruker’s TopSpin or other appropriate NMR processing software. The subfolders are named in accordance with the compound numbering in the associated research paper (Synthetic Approach to 2-Alkyl-4-quinolones and 2-Alkyl-4-quinolone-3-carboxamides Based on Common β-Keto Amide Precursors).</p> <p>Correspondence: angelov@uni-plovdiv.bg</p> <p> </p>
Data for: Making 1H-1H couplings more accessible and accurate with selective 2DJ NMR experiments aided by 13C satellites
<p><sup>1</sup>H-<sup>1</sup>H coupling constants are one of the primary sources of information for NMR structural analysis. Several selective 2DJ experiments have been proposed that allow their individual measurement at pure shift resolution. However, all these experiments fail in the not uncommon case when coupled protons have very close chemical shifts. Firstly, the coupling between protons with overlapping multiplets is inaccessible due to the inability of a frequency-selective pulse to invert just one of them. Secondly, the strong coupling condition affects the accuracy of coupling measurements involving third spins. These shortcomings impose a limit on the effectiveness of state-of-the-art experiments, such as G-SERF or PSYCHEDELIC. Here, we introduce two new and complementary selective 2DJ experiments that we coin SERFBIRD and SATASERF. These experiments overcome the aforementioned issues by utilizing the <sup>13</sup>C satellite signals at natural isotope abundance, which resolve the chemical shift degeneracy. We demonstrate the utility of these experiments on the tetrasaccharide stachyose and the challenging case of norcamphor, for the latter achieving measurement of all <em>J</em><sub>HH</sub> couplings while only few were accessible with PSYCHEDELIC. The new experiments are applicable to any organic compound and will prove valuable for configurational and conformational analyses.</p> <p>This deposit contains Bruker pulse sequences of the SERFBIRD and SATASERF experiments, and the Bruker NMR experimental data. See the readme.pdf file for an overview of the latter.</p>
NMR data for Bis(ethanol) bis(4-benzoyl-1-(4-methoxybenzyl)-1H-pyrazol-5-olate)magnesium (17). 1H, 13C, HSQC
<p>NMP FAIRSpec example collection</p>
Amines-NMR data
<p>Raw NMR data for the article "A General Catalyst for the Base-Free Mono-N-Alkylation of Aromatic and Aliphatic Amines with Alcohols " published in Cell Reports Physical Science.</p> <p>The raw NMR data files for all compounds reported in the article are included. The numbering corresponds to those in the article.</p> <p>Each parent folder contains subfolders with different files. In order to process this data, the full parent folder must be dragged into either Mestrenova or Topspin and then the data is automatically processed. If the name of the raw data files are renamed, the software (<a href="https://mestrelab.com/">Mestrenova</a> or <a href="https://www.bruker.com/en/products-and-solutions/mr/nmr-software/topspin.html">Topspin</a>) will not be able to process the files. </p>
Supplementary data frames, AlphaFold models, Normal Mode Analysis (NMA) Data, and NMA of Corresponding NMR Ensembles in the S2RCI, MD, and S2 Datasets for "Gradations in protein dynamics captured by experimental NMR are not well represented by AlphaFold2 models and other computational metrics"
<h1><strong>Changes applied to V2</strong></h1> <p>In addition to the supplementary dataframes and AlphaFold models from each dataset in V1, V2 includes the additional data outlined below.</p> <p>The <strong>S2RCI</strong> and <strong>MD</strong> datasets include comprehensive analyses of AlphaFold2 models (both before and after truncation). These datasets feature: </p> <ul> <li><strong>AlphaFold2 Models</strong>: Both original and truncated structures. </li> <li><strong>WEBnma Modes</strong>: `modes.txt` files generated from WEBnma analysis, available for both non-truncated and truncated AF2 models. </li> <li><strong>Root-Mean-Square-Fluctuations (RMSF)</strong>: Profiles calculated before and after truncation of AF2 models. </li> <li><strong>NMR Data: Normal Mode Analysis (NMA)</strong>: Performed on corresponding NMR ensembles (see below). </li> </ul> <p> </p> <p>The <strong>NMR Data</strong> of NMA in these datasets includes: </p> <ul> <li>NMR ensembles </li> <li>Individual NMR models extracted from each ensemble </li> <li>STRIDE secondary structure calculations per-individual NMR models</li> <li>RMSF profiles per-individual NMR models</li> </ul> <p>For detailed information, please refer to the `Readme.txt` file within each corresponding folder. </p> <p>The <strong>S2 dataset</strong> includes all the features listed above, except for the NMR analysis.</p>
NMR data for (NPA)6Zn3(H2O)2 in Synthesis, structural analysis, and docking studies with SARS-CoV-2 of a trinuclear zinc complex with N-phenylanthranilic acid ligands
<p><sup>1</sup>H, <sup>13</sup>C, COSY, HMBC, and HSQC NMR data in fid format for (NPA)<sub>6</sub>Zn<sub>3</sub>(H<sub>2</sub>O)<sub>2</sub> (NPA = 2-(phenylamino) benzoate) in DMSO-<em>d</em><sub>6.</sub></p>
Automated metabolic assignment: Semi-supervised learning in metabolic analysis employing two dimensional Nuclear Magnetic Resonance (NMR)
<p>This dataset is related to the paper <strong>“Automated metabolic assignment: Semi-supervised learning in metabolic analysis employing two dimensional Nuclear Magnetic Resonance (NMR)”.</strong></p> <p>https://www.sciencedirect.com/science/article/pii/S2001037021003792?via%3Dihub</p> <p>The dataset comprises horizontal and vertical frequencies of 2D NMR TOCSY of breast cancer-tissue sample. 2D TOCSY was acquired by employing a broadband high resolution 600.13 MHz (B0 = 14.1 T) NMR Bruker spectrometer (AVANCE III 600 with the Bruker magnet ASCEND 600) supported with the room temperature probe (BBO model-Bruker) and Magic Angle Spinning (MAS) probehead. 1D and 2D NMR spectra acquisition and processing were achieved by using the TopSpin software package 3.6.</p> <p>There are two files:</p> <p><strong>BreastCancerMetabolites.csv:</strong></p> <p>First column: numerical labels of the metabolites. Each number represent a metabolite. In total, there are 27 metabolites with multiple multiplets per metabolite.</p> <p>Second and third column: Horizontal and vertical frequencies for each metabolite.</p> <p><strong>Labels.csv:</strong></p> <p>The corresponding metabolites names.</p> <p> </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>
Automated Qualitative and Quantitative Analysis of Complex Forensic Drug Samples using 1H NMR
<p>Dataset to accompany the manuscript "Automated Qualitative and Quantitative Analysis of Complex Forensic Drug Samples using <sup>1</sup>H NMR"</p>
NMR data of Lanostane Type Triterpenoids isolated from Leplaea mayombensis
<p>This folder contains NMR datasets of new compounds described in the publication<em> </em>entitled: <strong>Antiplasmodial and Cytotoxic Activity of Lanostane Type Triterpenoids isolated from <em>Leplaea mayombensis</em></strong></p> <p> </p> <p>NMR processing : Topspin 4.1.13</p> <p> </p>
Data for: Nawrocka et al., Variable-temperature NMR spectroscopy for metabolite identification in biological materials, RSC Adv., 2021, 11, 35321, DOI: 10.1039/d1ra05626c
<p>Raw NMR spectrometer data (Varian/Agilent format) for the paper Nawrocka et al., Variable-temperature NMR spectroscopy for metabolite identification in biological materials, RSC Adv., 2021, 11, 35321, DOI: 10.1039/d1ra05626c</p> <p>Includes variable-temperature series for artificial and natural mixtures of metabolites and spectra of separate metabolites.</p>
Chemical shift imaging by NMR metabolomics
<p>This repository contains the point-wise binned NMR spectra as well as the data analysis R-code for the study "Chemical shift imaging by NMR metabolomics using in tube extraction and slice selection." by Silvio Waschina (Kiel University), Karsten Seeger (University of Lübeck).</p>
Human thymidylate synthase NMR relaxation data
<p>Table of intensities of NMR signals of human thymidylate synthase in multiple bound forms from several NMR relaxation experiments. Bound forms studied include apo, dUMP (substrate) bound, TMP (product) bound, as well as apo and dUMP bound N-terminal truncation. Experiments include methyl 13C MQ and SQ CPMG, CHD2 methyl 13C CEST, CHD2 methyl 2H R2, solvent PRE, backbone amide RDC, and 15N relaxation. Details of the data collection can be found in the associated publication.</p>
Supporting data for manuscript describing Slice and Dice method to measure NMR relaxation with nested experiments
<p>This is a supporting dataset for the manuscript "Slice and Dice: Nested Spin-lattice Relaxation Measurements" by W. Trent Franks, Jacqueline Tognetti and Józef R. Lewandowski.</p> <ul> <li><strong>NMR_data.zip : </strong>Raw NMR data in the Bruker format for the experiments presented in the manuscript. The file expands to a directory called "Raw NMR Data" that contains: <ul> <li>ReadMe_NMR_data.txt - describing the datasets included in the file.</li> <li>Record 1: <sup>13</sup>C<sup><span class="math-tex">\(^\alpha\)</span></sup> individual experiment. Pulse program name: hRCH_CT1</li> <li>Record 2: <sup>13</sup>C' individual experiment. Pulse program name: hCOcaH_SP_T1</li> <li>Record 3: <sup>15</sup>N individual experiment. Pulse program name: hRNH_NT1b</li> <li>Record 10: <sup>13</sup>C<span class="math-tex">\(^\alpha\)</span> + <sup>13</sup>C' + <sup>15</sup>N Slice & Dice experiment. Pulse program name: hR[COca,Ca,N]Ha_T10818 corresponding to the final sequence: hR[N,COca,Ca]HR_T1</li> </ul> </li> <li><strong>Pulse_program.zip</strong>: The pulse program and include file for the Slice and Dice experiment described in the manuscript. The pulse program in Bruker format (war.hR[COca,Ca,N]H_T1 - this is a text file that can be opened with any text editor) was tested on a Bruker Avance III HD console. Both the pulse program file, war.hR[COca,Ca,N]H_T1, and include file, HCN_defs.incl, need to be placed in the pulse program directory (/opt/topspinXX/exp/stan/nmr/lists/pp/user where XX is replaced with the version of Topspin). The file expands to a directory "Pulse_program_incl" that contains: <ul> <li>war.hR[COca,Ca,N]H_T1 - pulse program</li> <li>HCN_defs.incl - include file</li> <li>ReadMe_SliceDice_pp.txt - details on how to set up the experiment.</li> </ul> </li> <li><strong>HowToProcessSliceAndDice.pdf</strong> : Instructions on how to process Slice and Dice experiment in Topspin.</li> <li><strong>MultiR1list.zip: </strong>A program written in Python 3 required to calculate delay lists for the nested experiment to be included in the pulse program. The file expands to a directory MultiT1list directory that contains: <ul> <li>MultiT1list.py - the program</li> <li>ReadMe_MultiT1list.txt - instructions on how to use the program</li> </ul> </li> <li><strong>SNDProcguide.py.zip</strong>: A program written in Python 2 (SNDProcguideV2.py), which generates macro for processing and sorting 2D planes in Topspin. The script also provides some tips on setting parameters for different 2Ds and sorted lists of relaxation delays. Example output of the script is also included. The parameters in the script are set for the supplied example data.</li> <li><strong>HowToProcess.mp4</strong> - a video working through an example of processing Slice and Dice data.</li> </ul> <p> </p> <p> </p>
NMR titration experiments that study binding of a NIR emitting osmium polypyridyl probe to cMYC and hTel G-quadruplex DNA
<p>1D and 2D NMR spectra of cMYC and hTel G-quadruplex DNA and their complexes with Λ-<strong> </strong>and Δ<strong>-</strong>enantiomers of the osmium polypyridyl probe [Os(TAP)<sub>2</sub>(dppz)]<sup>2+</sup>. Spectra were recorded on a 600 MHz NMR spectrometer with 70 mM KCl, 20 or 25 mM K-phosphate buffer, pH 7, 298 K, in 90% H<sub>2</sub>O and 10% D<sub>2</sub>O at 25 °C.</p>
Supplementary data: A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR
<p><strong>Content:</strong></p> <p>This dataset provides supplementary data to "A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR". It contains trained Neural Network Potentials (NNP), energy and force data used for accuracy evaluation of the NNPs. Energy and forces are stored as ASE trajectory files (traj), readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE). In addition, this repository contains the generated training database with DFT (SCAN+D3(BJ)) energies and forces as SchNetPack1.0 database (SiAlOHNa.db) file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>. Also, the structure files used to calculate NMR properties are involved.</p> <ul> <li>"nnps.zip" - (pytorch) NNP model files (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>)</li> <li>"SiAlOHNa.db" - DFT (SCAN+D3(BJ)) training database as SchNetPack1.0 database file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li> <li>"error_stats.zip" - traj files storing energies/forces at the DFT (SCAN+D3(BJ)) and NNP level for all test simulations to calcuate energy/force errors</li> <li>"Structures_CHA17.zip" - the structures files of CHA(17). </li> </ul>
1H NMR spectra of commercial honey from 400 and 700 MHz spectrometers and tables with data after processing and binning
<p>Datasets contain the 1H NMR original raw spectral data (Bruker format) of commercial honey from 400 MHz and 700 MHz NMR spectrometers and Tables (.xlsx) with data after processing and binning.</p> <p> </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.