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.
175
datasets available to search
ShareScore release 0.9.0
Dataset results
175 results for “Lipidomics”
Four lipidomics datasets (mouse liver, mouse pancreatic islets, mouse soleus muscle and mouse visceral adipose tissue), generated for the publication Mehl et al., "A multiorgan map of metabolic, signalling, and inflammatory pathways that coordinately control fasting glycemia in mice"
<p>Mehl, Thorens et al present a multiomics study aimiing to<span> identify the pathways that are coordinately regulated in pancreatic </span><span>b</span><span>-cells, muscle, liver, and fat to control fasting glycemia we fed C57Bl/6, DBA/2 and Balb/c mice a regular chow or a high fat diet for 3, 10 and 30 days. We measured fasted glycemia, insulinemia and whole-body insulin resistance. Transcriptomic and lipidomic analysis were used in a data fusion approach to identify organ-specific pathways related to the glycemic levels across all conditions investigated. In pancreatic islets, constant insulinemia despite higher glycemic levels were associated with reduced expression of mRNAs encoding hormone and neurotransmitter receptors as well as OXPHOS, cadherins, integrins and gap junction proteins. Higher glycemia and whole-body insulin resistance were associated, in muscle, with reduced expression of mRNAs encoding insulin signaling proteins and enzymes of the glycolysis, Krebs’ cycle and OXPHOS pathways, as well as endocytosis and exocytosis proteins; in hepatocytes, with lower expression of mRNAs of the insulin signaling pathway, of branched chain amino acid catabolism and of OXPHOS; in adipose tissue, with increased expression of mRNAs of innate immunity and lipid catabolism. These data provide a map of the pathways that are coordinately recruited in the investigated tissues to control fasting glycemia and a resource for further studies of interorgan communication in glucose homeostasis. </span></p>
Lipidomics LC-MS analysis support tools for outlier detection
<p>Identification of features with high levels of confidence in liquid chromatography-mass spectrometry (LC MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in bioinformatics work, and highlights the importance of data-driven outlier detection in assessing spectral outputs – here demonstrated using a machine learning approach based on support vector machine regression combined with leave-one-out cross validation – as well as manual curation, in order to identify software-driven errors driven by closely related lipids and by co-elution issues.</p> <p>The lipidomics case study dataset used in this work analysed a lipid extraction of a human pancreatic adenocarcinoma cell line (PANC-1, Merck, UK, cat no. 87092802) analysed using an Acquity M-Class UPLC system (Waters, UK) coupled to a ZenoToF 7600 mass spectrometer (Sciex, UK). Raw output files are included alongside processed data using MS DIAL (v4.9.221218) and Lipostar (v2.1.4) and a Jupyter notebook with Python code to analyse the outputs for outlier detection.</p>
T1D-lipidome: Database of lipidomic aberrations during the pathogenesis of type 1 diabetes (T1D)
<p>This is the<strong> living database</strong> of <strong>lipidomic aberrations</strong> during the <strong>pathogenesis of type 1 diabetes</strong> (T1D).</p> <p>The database has been collected from scientific publications that report abnormalities related to the onset of T1D. In practice, this either means:</p> <ol> <li>lipids that are aberrated in blood samples collected from persons, who are later known to have been diagnosed with T1D,</li> <li>lipids that are aberrated in blood samples collected from persons, who are have islet auto-antibodies (IAA-positive), or</li> <li>lipids that are associated with the deterioration of insulin secretion in blood samples collected from persons recently diagnosed with T1D.</li> </ol> <p>This database is described in the following publication. Please cite the publication, if you use the database or related code:</p> <p><strong>Citation</strong></p> <p>Tommi Suvitaival. <strong>Lipidomic Abnormalities During the Pathogenesis of Type 1 Diabetes: a Quantitative Review</strong>. <em>Current Diabetes Reports</em>. 20, 46 (2020). <a href="http://dx.doi.org/10.1007/s11892-020-01326-8">http://dx.doi.org/10.1007/s11892-020-01326-8</a></p> <p><strong>Acknowledgement</strong></p> <p>This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115797 (<a href="https://www.innodia.eu/">INNODIA</a>). This Joint Undertaking receives support from the Union’s Horizon 2020 research and innovation programme and “EFPIA”, ‘JDRF” and “The Leona M. and Harry B. Helmsley Charitable Trust”.</p>
MetabolACE-Metabolomics & Lipidomics Dataset 1
<p>Analysis of intact lipids in Mock, Scramble and NAA40-KD cells using high-resolution mass spectrometry</p>
Lipidomic Data of Mycoplasma mycoides and JCVI-Syn3A grown on defined lipid diets
<p>Shotgun Lipidomics of four conditions: Mycoplasma mycoides grown on a 2FA + Cholesterol diet, a POPC + Cholesterol diet, a Diether PC + Cholesterol diet, and JCVI-Syn3A grown on a Diether PC + Cholesterol diet. All data made with three biological replicates. Lipids extracted from cells using the Bligh-Dyer protocol. Lipids analyzed by Lipotype with mass spectrometry based analysis. </p>
Spatially mapping the baseline and bisphenol-A exposed Daphnia magna lipidome using desorption electrospray ionisa-tion - mass spectrometry
<p>Data from desorption electrospray ionisation - mass spectrometry of <em>Daphnia magna</em> tissue section from control and daphnids exposed to 5 ppm of bisphenol A over their 7<sup>th</sup> adult instar, specifically four sampling points; 8, 24, 48 and 72 h after the 6<sup>th</sup> brood, as well as data acquired from a blank DESI slide.</p> <p>Data is provided in the form of *imzML files with the associated *.ibd of the same name.</p>
Metabolic and lipidomic data of patients with idiopathic pulmonary fibrosis and healthy volunteers
<p>The metabolomic / lipidomic datasets used in the manuscript draft entiteld: </p> <p>"Changes in Serum Metabolomics in Idiopathic Pulmonary Fibrosis and effect of approved antifibrotic medication"</p> <p>by</p> <p>Benjamin Seeliger, Alfonso Carleo, Pedro David Wendel-Garcia, Jan Fuge, Ana Montes Worboys, Sven Schuchardt, Maria Molina-Molina and Antje Prasse</p> <p>Data is untransformed and missing data were imputated. All values are in µmol/L.</p>
Rapid assessment of lipidomics sample quality and quantity using attenuated total reflectance Fourier-transform infrared spectroscopy
<p>In this work, we aimed to develop a simple lipid quality and quantification method for biological lipid extracts, as a step in lipidomics workflows, with minimal sample requirement. We chose FTIR spectroscopy with an Attenuate Total Reflectance (ATR) sampling method as it requires just 1 microliter of MS-ready sample without additional sample preparation. We validated the proposed lipidomics sample quality control workflow using a set of plasma samples (n=107, with 3-4 technical replicates) with comparison to LC-MS-based lipidomics. The following file contains the resulting spectra acquired by ATR-FTIR spectrometry for these plasma samples, standard curves and contaminated samples used for method development. Spectrometer was ambient blanked and detector cleaned between each measurement. Lipid samples were extracted by butanol-methanol (3:1) precipitation, and dried directly onto the ATR-FTIR detector. Absorbance was measured between 4,000 and 650 cm-1 wavenumbers, at a resolution of 8cm-1. Each spectra has been baseline corrected (whole spectra).</p>
LipidMS v3.0.3: source code and example of lipidomics dataset for human serum
<p>Source code and example dataset for LipidMS v3.0.3: a commercially available pooled human serum sample was analyzed in positive and negative detection modes and using MS1, DIA and DDA approaches. The obtained datasets were processed using LipidMS v3.0, MS-DIAL v4.80 or a combination of data pre-processing in XCMS v3.16 and lipid annotation in LipidMS v3.0.</p> <p>This repository contains:</p> <p>- Raw data for positive and negative polarities using MS scan, DIA and DDA acquisition modes.</p> <p>- R scripts for processing with LipidMS v3.0.3 and XCMS v3.16.1 and parameters used for processing with MS-DIAL v4.80.</p> <p>- Source code for LipidMS v3.0.3.</p> <p>- Results obtained for the 3 different softwares employed.</p> <p>- Tutorials for LipidMS R package and online application.</p> <p>- Human pooled serum analysis</p> <ul> <li>Raw data for positive and negative polarities using MS scan, DIA and DDA acquisition modes for a human pooled serum sample with or without the addition of 68 lipid standars</li> <li>Results for the data processing and annotation of the lipid standards using LipidMS 3.0, XCMS 3.16 and MS-DIAL 4.80</li> <li>Results for the manual curation of the total lipid annotations provided by both LipidMS 3.0 and MS-DIAL 4.80</li> </ul>
Research data supporting "Correlated heterospectral lipidomics for biomolecular profiling of remyelination in multiple sclerosis"
<p>Research data supporting the paper:</p> <p>Bergholt, M.S. et al., "Correlated heterospectral lipidomics for biomolecular profiling of remyelination in multiple sclerosis", ACS Central Science, 2017, DOI: 10.1021/acscentsci.7b00367.</p>
Trapped ion mobility spectrometry-guided molecular discrimination between plasmalogens and other ether lipids in lipidomics experiments
<p>Supplementary Dataset for the manuscript "Trapped ion mobility spectrometry-guided molecular discrimination between plasmalogens and other ether lipids in lipidomics experiments" under preparation for bioRxiv submission.<br>Data is packed into a zip archive according to ZENODO upload limitations.<br>in the top folder the actual analysis and respective files, as described in the publications supplementary materials can be found as <em>PLOP2 </em>folder (including raw data etc.).<br>The additional images explain the repo layout in a sketched form: <br>Additionally also for data readout the used <em>docker-compose.yml </em>and a github clone of the important <em>timsr </em>package is included.<br>PLEASE READ the README!.<br><br>Additionally the file `Calibration-2021-08-31_11-44-22.pdf` contains the calibration report, and `PLOP4_method.pdf` a hystar report of the used methodology.<br><br>For LSI Reporting Checklist see DOI: 10.5281/zenodo.13963972</p>
Global cellular proteo-lipidomic profiling of diverse lysosomal storage disease mutants using nMOST
<div> <div> <div> <div> <p>Lysosomal storage diseases (LSDs) comprise ~50 monogenic disorders marked by the buildup of cellular material in lysosomes, yet systematic global molecular phenotyping of proteins and lipids is lacking. We present a nanoflow-based multi-omic single-shot technology (nMOST) workflow that quantifies HeLa cell proteomes and lipidomes from over two dozen LSD mutants. Global cross-correlation analysis between lipids and proteins identified autophagy defects, notably the accumulation of ferritinophagy substrates and receptors, especially in NPC1-/- and NPC2-/- mutants, where lysosomes accumulate cholesterol. Autophagic and endocytic cargo delivery failures correlated with elevated lyso-phosphatidylcholine species and multi-lamellar structures visualized by cryo-electron tomography. Loss of mitochondrial cristae, MICOS-complex components, and OXPHOS components rich in iron-sulfur cluster proteins in NPC2-/- cells was largely alleviated when iron was provided through the transferrin system. This study reveals how lysosomal dysfunction affects mitochondrial homeostasis and underscores nMOST as a valuable discovery tool for identifying molecular phenotypes across LSDs.</p> </div> </div> </div> </div>
Simulation systems of: "Free energies of membrane stalk formation from a lipidomics perspective"
<p><strong>Simulation systems of: </strong></p> <p>Free energies of membrane stalk formation from a lipidomics perspective</p> <p>Chetan S. Poojari, Katharina C. Scherer, Jochen S. Hub</p> <p>Nature Communications, 12, 6594 (2021), <a href="https://doi.org/10.1038/s41467-021-26924-2">https://doi.org/10.1038/s41467-021-26924-2</a></p> <p> </p> <p><strong>First published as a preprint manuscript in BioRxiv as:</strong></p> <p>Free energies of stalk formation in the lipidomics era</p> <p>Chetan S. Poojari, Katharina C. Scherer, Jochen S. Hub,</p> <p>BioRxiv, https://www.biorxiv.org/content/10.1101/2021.06.02.446700v1, 2021</p> <p>The archive contains</p> <ul> <li>starting conformations of double-membrane systems</li> <li>topologies</li> <li>MD parameter files</li> </ul> <p>Running the simulations requires a modified version of GROMACS, which implements the chain coordinate available at GitLab:</p> <p><a href="https://gitlab.com/cbjh/gromacs-chain-coordinate">https://gitlab.com/cbjh/gromacs-chain-coordinate</a></p>
Revealing the lipidome and proteome of Arabidopsis thaliana plasma membrane
<p>This table contains peaks aera values from GC-MS, TLC-GC-MS and LC-MS for characterization of Arabidopsis thaliana plasma membrane. These data were used for Fig. 6, 7, 8, 9 and S1, S2, S3 and S4 of Bahammou et al. 2023: Revealing the lipidome and proteome of Arabidopsis thaliana plasma membrane</p>
Dupilumab-PEdiatric Skin Barrier Function and LIpidomics STudy in Patients With Atopic Dermatitis
ClinicalTrials.gov study NCT04718870. IPD Sharing: YES. Countries: 2. Publications: 0.
Data from: Enzyme polymorphism, oxygen and injury: a lipidomic analysis of flight-induced oxidative damage in a SDH-polymorphic insect
When active tissues receive insufficient oxygen to meet metabolic demand, succinate accumulates and has two fundamental effects: it causes ischemia-reperfusion injury while also activating the hypoxia-inducible factor pathway (HIF). The Glanville fritillary butterfly (Melitaea cinxia) possesses a balanced polymorphism in Sdhd, shown previously to affect HIF pathway activation and tracheal morphology and used here to experimentally test the hypothesis that variation in succinate dehydrogenase affects oxidative injury. We stimulated butterflies to fly continuously in a respirometer (3 min duration), which typically caused episodes of exhaustion and recovery, suggesting a potential for cellular injury from hypoxia and reoxygenation in flight muscles. Indeed, flight muscle from butterflies flown on consecutive days had lipidomic profiles similar to rested paraquat-injected butterflies, but distinct from rested untreated butterflies. Many butterflies showed a decline in flight metabolic rate (FMR) on Day 2, and there was a strong inverse relationship between the ratio of Day 2 to Day 1 FMR and the abundance of sodiated adducts of phosphatidylcholines and coenzyme Q (CoQ). This result is consistent with elevation of sodiated lipids caused by disrupted intracellular ion homeostasis in mammalian tissues after hypoxia-reperfusion. Butterflies carrying the Sdhd M allele had higher abundance of lipid markers of cellular damage, but the association was reversed in field-collected butterflies, where focal individuals typically flew for seconds at a time rather than continuously. These results indicate that Glanville fritillary flight muscles can be injured by episodes of high exertion, but injury severity appears to be determined by an interaction between SDH genotype and behavior (prolonged vs. intermittent flight).
Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes
<p>This file contains all the data relevant to the manuscript titled “Unravelling Plankton Adaptation in Global Oceans through the Analysis of Lipidomes,” as well as all the code used to generate the data and the figures presented in the manuscript.</p>
Lipidomic data of the kidney cortex from diabetic mice fed MUFA-HFD and SFA-HFD
<p><span>In diabetic patients, </span><span>dyslipidemia </span><span>frequently contributes to organ damage such as </span><span>diabetic kidney disease (DKD). DKD is associated with excessive renal deposition of triacylglycerol (TAG) in lipid droplets (LD). Yet, it is unclear whether LDs play a protective or damaging role and how this might be influenced by dietary patterns. By using a diabetes mouse model, we find here that high-fat diet enriched in the unsaturated oleic acid (OA) caused more lipid storage in LDs in renal proximal tubular cells (PTC) but less tubular damage than a corresponding butter diet with the saturated palmitic acid (PA). In order to study the changes in the lipidome, we performed shotgun lipidomics on the kidney cortex of these mice.</span></p>
Lipidomic data of iRECs treated with palmitic acid and oleic acid
<p>In diabetic patients, dyslipidemia frequently contributes to organ damage such as diabetic kidney disease (DKD). DKD is associated with excessive renal deposition of triacylglycerol (TAG) in lipid droplets (LD). In order to identify the changes in the lipidome of proximal tubules exposed to high levels of fatty acids and the role that LDs formation play in this context, we treated induced Renal Epithalial Cells (iRECS) <span>with BSA, BSA-PA (Palmitic Acid), BSA-OA (Oleic Acid), BSA-PA/OA, BSA + DGAT1/2 inhibitors, BSA-PA + </span>DGAT1/2 inhibitors and BSA-PA/OA + DGAT1/2 inhibitors. </p>
MIGA2 lipidomics datasheet
<p>Lipidomics analysis datasheet of human MIGA2 soluble portion (purified from Expi293 cells and gel filtrated).</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.