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5 results for “NIST”
Liquid Chromatography - Tandem Mass Spectrometry (LC-MS/MS) and Gas Chromatography - Mass Spectrometry (GC-MS) Reference Libraries from Global Natural Products Social Molecular Networking (GNPS) and National Institute of Standards and Technology (NIST) WebBook Processed for Spectral Library Matching
<div>In order to obtain a high-quality LC-MS/MS reference database for spectral library matching, we selected 22 high-quality GNPS tandem mass spectrometry databases generated under the positive ion mode. Further preprocessing similar to Huber et al involving mass-to-charge (m/z) and intensity filtering yields the database found in the file LCMS_GNPS_reference_library.csv which contains 14,705 electrospray ionization (ESI) mass spectra, each of which corresponds to a unique compound. The NIST WebBook database was used to construct GC-MS database contained in the file GCMS_NIST_WebBook.csv. This database contains 23,721 electron ionization (EI) mass spectra, each of which corresponds to a unique non-hyphenated Chemical Abstract Service (CAS) Registry Number.</div> <div> </div> <div>Both LC-MS/MS and GC-MS databases are organized into three columns: one for the identifier, one for the m/z values, and one for the intensity values. For example, if spectrum A has 20 ion fragments, then there will be 20 rows corresponding to spectrum A in the corresponding database with the identifier A repeated 20 times with the corresponding m/z and intensity values.</div>
Datasets of "Differences in the stool metabolome between vegans and omnivores: analyzing the NIST stool reference material" publication
<p>To gain confidence in results of omic-data acquisitions, methods must be benchmarked by validated quality control materials. We here report data combining both untargeted and targeted metabolomics assays for the analysis of four new human fecal reference materials developed by the U.S. National Institute of Standards and Technologies (NIST) for metagenomics and metabolomics measurements. These reference grade test materials (RGTM) were established by NIST based on two different diets and two different samples treatments: homogenized fecal matter from subjects eating vegan diets, stored and submitted in either lyophilized (RGTM 10162) or aqueous form (RGTM 10171); secondly, homogenized fecal matter from subjects eating omnivore diets, stored and submitted in either lyophilized (RGTM 10172) or aqueous form (RGTM 10173). We used four untargeted metabolomics assays (lipidomics, primary metabolites, biogenic amines and polyphenols) and one targeted assay on bile acids.</p>
Neutron powder diffraction from NIST 660c LaB6 standard for calibration of Wombat high-intensity neutron powder diffractometer
<p>Calibration data for the Wombat high intensity powder diffractometer, ANSTO, collected at a nominal wavelength of 1.64A from NIST 660c LaB<sub>6</sub> standard using the [224] reflection from a single crystal Ge monochromator, [335] cut. Note that B in this standard is enriched to 99% with isotope <sup>11</sup>B. The sample was loaded in a 6mm diameter vanadium cylindrical sample can.</p>
IDSL.CSA FSDBs for publicly available spectra from NIST and MoNA databases
<p>IDSL.CSA fragmentation spectra databases (FSDBs) for publicly available spectral databases. </p> <p>FSDB is a R list object with elements describing various features to speed up libraries searches. </p>
Datasets for the Tiwary Lab contribution to the NIST JARVIS database
<p>ala2.zip:</p> <ul> <li>test -- Alanine dipeptide in vacuum, simulated using GROMACS 2020.2 at 450 K using the amber99sb-ildn force field for 1 microsecond, unbiased</li> <li>ref -- Alanine dipeptide in vacuum, simulated using GROMACS 5.0 at 450 K using the amber03 force field for 800 ns, unbiased</li> </ul> <p>ala3.zip:</p> <ul> <li>test -- Alanine tetrapeptide in vacuum, simulated using GROMACS 2021.4 at 400 K using the amber99sb-ildn force field, three 1 microscond replicates, unbiased</li> <li>ref -- Alanine tetrapeptide in vacuum, simulated using GROMACS 5.0.4 at 400 K using the amber99sb-ildn force field for 1 microsecond, unbiased (trajectory data not included)</li> </ul> <p>aib9.zip:</p> <ul> <li>test -- Alpha-aminoisobutyric acid-9 solvated in TIP3P, simulated using GROMACS 2018.8 at 500 K using the CHARMM36m force field for 200 ns, unbiased</li> <li>ref -- Alpha-aminoisobutyric acid-9 solvated in TIP3P, simulated using GROMACS 2018.8 at 400 K using the CHARMM36m force field for 714 ns, biased using well-tempered metadynamics as described in <a href="https://pubs.acs.org/doi/10.1021/acs.jctc.2c00058">https://pubs.acs.org/doi/10.1021/acs.jctc.2c00058</a> (trajectory data not included)</li> </ul>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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OpenNeuro
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