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15 results for “non-targeted metabolome”
mzrtsim: Raw Data Simulation for Reproducible Gas/Liquid Chromatography–Mass Spectrometry Based Non-targeted Metabolomics Data Analysis
<p>All the data for 'mzrtsim: Raw Data Simulation for Reproducible Gas/Liquid Chromatography–Mass Spectrometry Based Non-targeted Metabolomics Data Analysis'</p> <p>sim.zip is stimulated data for intensity cutoff 0.05. simxcms.csv is peak intensity profiles for their simulated peaks.</p> <p>sim3.zip are simulated data for normal/leading/tailing peaks with tailing factor of 1, 0.8, and 1.5, respectively.</p> <p>All the csv files begin with sim3 are extracted peaks list from the sim3.zip with corresponding data analysis software.</p> <p>csv.zip recorded the m/z, retention time, intensity, and compounds name for simulated compound for each condition (sim.zip and sim3.zip).</p> <p>sep1.mzML: simulation for 8 isomers with similar m/z while different retention times. 7 peaks are non baseline separation peaks. Peaks profile is saved in spe1.csv file.</p> <p>xcms.csv, mzmine.csv, openms.csv: peaks found in sep1.mzML by xcms, mzmine 4.5 and openms, respectively.</p> <p>R code: <a href="https://github.com/yufree/democode/blob/master/meta/simfin.R">https://github.com/yufree/democode/blob/master/meta/simfin.R</a></p> <p>Website of mzrtsim package: https://yufree.github.io/mzrtsim/</p>
Non-Targeted Metabolomics of a Phytoplankton Bloom in the California Current Ecosystem 1706
<p>Non-Targeted LC-MS/MS based Metabolomics of SPE (PPL) extracts of a Phytoplankton Bloom in the California Current Ecosystem 1706</p>
Non-targeted metabolomics-based molecular networking enables the chemical characterization of Rumex sanguineus, a wild edible plant
<p>This dataset delves into the chemical composition of Rumex sanguineus employing non-targeted metabolomics and Feature-Based Molecular Networking (FBMN), with compound annotation facilitated by SIRIUS. Utilizing UHPLC-HRMS, we conducted comprehensive analyses on samples extracted from Rumex roots, stems, and leaves, further enhancing our insights through molecular networking.</p>
Non-targeted metabolome profiling in splenic monocyte-derived dendritic cells from Plasmodium chabaudi-infecetd mice
<p>Spleens from mice infected with Plasmodium chabaudi were processed and stained for localization of monocyte-derived dendritic cells (MODCs) by flow cytometry. The markers utilized were: Live/Dead, F4/80, CD11b, DCSign, MHCII, CD11c and CD3. After sorted out, MODCs were frozen in liquid nitrogen, followed by metabolite extraction, as recommended by The Metabolomics Facility at MD Anderson. Metabolites were extracted using ice-cold 0.1% Ammonium hydroxide in 80/20 (v/v) methanol/water. Extracts were centrifuged at 17,000 g for 5 min at 4°C, and supernatants were transferred to clean tubes, followed by evaporation to dryness under nitrogen. Dried extracts were reconstituted in deionized water, and 5 μL was injected for analysis by ion chromatography (IC)-MS. IC mobile phase A (MPA; weak) was water, and mobile phase B (MPB; strong) was water containing 100 mM KOH. A Thermo Scientific Dionex ICS-5000+ system included a Thermo IonPac AS11 column (4 µm particle size, 250 x 2 mm) with column compartment kept at 30°C. The autosampler tray was chilled to 4°C. The mobile phase flow rate was 350 µL/min and gradient from 1mM to 100mM KOH was used. The total run time was 60 min. To assist the desolvation for better sensitivity, methanol was delivered by an external pump and combined with the eluent via a low dead volume mixing tee. Data were acquired using a Thermo Orbitrap Fusion Tribrid Mass Spectrometer under ESI negative ionization mode at a resolution of 240,000.</p>
Statistical Analysis of Feature-based Molecular Networking Results from Non-Targeted Metabolomics Data
<p>This folder contains the following used for the publication:</p><ul><li>MASSIVE Repositories: MSV000082312 and MSV000085786. This contains the original data in both .raw and .mzxml formats.</li><li>MZmine 3 files: The feature table (SD_BeachSurvey_GapFilled_quant.csv), the associated mgf file, the batch file (.xml) used for MZmine 3 to obtain the feature table, the mgf file for SIRIUS annotations (SD_BeachSurvey_SIRIUS_fixed.mgf)</li><li>SIRIUS and CANOPUS summary files (.tsv files)</li><li>FBMN Result files</li></ul>
Non-targeted metabolomics and transcriptomics reveal mechanisms of metabolic differences among roots, stems, and leaves of Cudrania tricuspidata
<p>We detected a total of 1254 metabolites from the three tissues of Cudrania roots, stems, and leaves, and all metabolites were annotated and classified into eight categories by the KEGG database: steroids, lipids, antibiotics, vitamins and cofactors, nucleic acids, peptides, carbohydrates, and organic acids. Flavonoid-rich roots and stems of Cudrania were significantly different from the transcripts of leaves. GO and KEGG enrichment analyses revealed that the differential genes were mainly enriched in Photosynthesis - antenna proteins, Zeatin biosynthesis, Flavone and flavonol biosynthesis, Monoterpenoid biosynthesis pathway. The expression of flavonoid and flavonol biosynthesis-related genes was significantly up-regulated in roots and stems. From the perspective of the differences in metabolites among roots, stems and leaves of Cudrania, it can provide a basis for revealing the material basis of the differences in medicinal properties and efficacy of different parts.</p>
Study on the Characteristics of Non-targeted Metabolomics and EEG of Delayed Neurocognitive Recovery in Elderly Patients
ClinicalTrials.gov study NCT05105451. IPD Sharing: NO. Countries: 1. Publications: 2.
2D-LC-MS/MS based non-targeted metabolomics of marine DOM (.raw files)
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2D-LC-MS/MS based non-targeted metabolomics of marine DOM (.mzML files)
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Non-Targeted Metabolomics of Cichorium Fermenation Extracts
<p>Non-targeted LC-MS/MS based metabolomics of fermentation time series of Cichorium extracts. </p>
Non-targeted microbial metabolomics (DDA) of extracts from methanotroph cocultures
<p>Non-targeted microbial metabolomics (DDA) of extracts from methanotroph cocultures</p>
Data from: Development, characterization and comparisons of targeted and non-targeted metabolomics methods
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Metabolic Engineering of Squalene Biosynthesis via Different Genomes Impacts Non-target Cellular Metabolomic and Transcriptomic Pathways
GEO Series GSE74103. Nicotiana tabacum. 8 samples. Type: Expression profiling by high throughput sequencing.
UPLC-QTOF/MS non-targeted metabolomic data of 22 male Eucommia ulmoides Oliv. flower core collections
<p>The upload files include five xlsx. worksheets and two zip. files, respectively,the list of voucher specimen samples for 22 male<em> E. ulmoides</em> flower core collections,the metabolite annotations and peak intensities of the ESI+ & ESI- mode,the normalized ion intensity matrix of the ESI+ & ESI- mode, and raw wiff. format data of the ESI+ & ESI- mode.</p>
Non-target Metabolomics - MeStaLeM Project (mzML)
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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.
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DANDI Archive for NWB datasets
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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.