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102 results for “spectrometry data”
Data from: In situ lipidomics of Staphylococcus aureus osteomyelitis using imaging mass spectrometry
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Data from: Direct measurement of fluorocarbon radicals in the thermal destruction of perfluorohexanoic acid using photoionization mass spectrometry
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Mass spectrometry data for: A small protein coded within the mitochondrial canonical gene nd4 regulates mitochondrial bioenergetics
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Fourier transform ion cyclotron resonance (FT ICR) mass spectrometry data
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Data from: Long-lived metabolic enzymes in the crystalline lens identified by pulse-labeling of mice and mass spectrometry
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Porcine cell-free system mass spectrometry compiled data sets
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Data for: Oligonucleotide mapping via mass spectrometry to enable comprehensive primary structure characterization of an mRNA vaccine against SARS-CoV-2
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Mass spectrometry data from: Deficiency in Galectin-3, -8, and -9 impairs immunity to chronic Mycobacterium tuberculosis infection but not acute infection with multiple intracellular pathogens
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Mass spectrometry data for interactive volcano plots - by van der Weegen et al.
<p>These datasets are generated by Yana van der Weegen et al. (2020) and part of the publication "The sequential and cooperative action of CSB, CSA and UVSSA targets the TFIIH complex to DNA damage-stalled RNA polymerase II" to be published in Nature Communications.</p> <p>The CSV files are used as input to generate (interactive) volcano plots, using the web app VolcanoNoseR. The code is archived here: https://zenodo.org/record/3625858</p> <p>The most up-to-date version of the interactive web app is available here: <a href="https://huygens.science.uva.nl/VolcaNoseR/">https://huygens.science.uva.nl/VolcaNoseR/</a></p>
Mass spectrometry data for interactive volcano plots - van der Weegen et al., 2020
<p>These datasets are generated by Yana van der Weegen et al. (2020) and part of the publication "The sequential and cooperative action of CSB, CSA and UVSSA targets the TFIIH complex to DNA damage-stalled RNA polymerase II" to be published in Nature Communications.</p> <p>The CSV files are used as input to generate (interactive) volcano plots, using the web app VolcanoNoseR. The code is archived here: https://zenodo.org/record/3625858</p> <p>The most up-to-date version of the interactive web app is available here: <a href="https://huygens.science.uva.nl/VolcaNoseR/">https://huygens.science.uva.nl/VolcaNoseR/</a></p> <p> </p> <p> </p>
Data from: Liquid chromatography-mass spectrometry (LC-MS) data of a multi-epitope peptibody with bFGF/VEGFA
<p><span><span><span><span><span><span><span><span><span><span><span>The <span><span><span>protein </span></span></span><span><span><span>primary </span></span></span><span><span><span>structure of the recombinant </span></span></span>Peptibody were investigated systematically by Liquid Chromatography-Mass Spectrometry (LC-MS)<span><span><span>. T</span></span></span><span><span>he 15 amino acids of N-terminal were </span></span>Met-Gln-Lys-Arg-Lys-Arg-Lys-Lys-Ser-Arg-Tyr-Lys-Ser-Gly-Gly and <span><span>the C-terminal was Lys (K</span></span><span><span>), the same as</span></span> the theoretical sequence. <span><span>With more </span></span><a><span class="15"><span>protease</span></span></a><span><span>s, the whole sequence was detected at the coverage of </span></span>trypsin 87.5%, <span><span>c</span></span><span><span>hymotrypsin</span></span> 75.3% and <span><span>Glu-C</span></span> 76.7%<span><span>. The </span></span>peptide-mapping could be used as an valuable standard to certify the complete expression and primary structure of Peptibody. The pI and MW were 8.93 and 37.415 kDa, within the errors allowed . The binding specificity after production were analyzed using anti-VEGFA and anti-His antibodies.</span></span></span></span></span></span></span></span></span></span></span></p>
Supplementary data to accompany "Abundant metabolite-matrix adducts illuminate the dark metabolome of MALDI-mass-spectrometry imaging datasets"
<p>This dataset accompanies the publication "Abundant metabolite-matrix adducts illuminate the dark metabolome of MALDI-mass-spectrometry imaging datasets". The dataset includes all files, scripts and results that are included in the associated publication.</p> <p>Spatial metabolomics using mass spectrometry imaging (MSI) is a powerful tool to map hundreds or thousands of metabolites across biological systems. One major challenge is the complexity of the data, which includes signals from experimental artifacts. Formation of adducts (<em>e.g. </em>with Na+or K+) or abundant matrix-cluster, in the case of matrix-assisted laser desorption ionization (MALDI)-MSI, strongly increase peak counts. We developed <em>mass2adduct</em>, a universally applicable tool for adduct abundance estimations in high-mass-resolution spatial metabolomics datasets. Our study illustrates that MALDI-MSI data density is remarkably driven by adduct formation and revealed a major influence of so far unrecognized metabolite-matrix adducts on total peak counts. Current data analyses neglect those matrix adducts and therefore overestimate total metabolite numbers, thereby inflating the dark metabolome size.</p> <p>mass2adduct zenodo doi (10.5281/zenodo.1405088)</p> <p>mass2adduct gihub: https://github.com/kbseah/mass2adduct</p>
Mass spectrometry data Spo11 and Msh4-1
<p>The procedure for Spo11 data is based on the peptide intensities reported in the evidence file provided by MaxQuant:</p> <p>1) peptide intensities are normalized using the variance stabilization transformation (bioconductor package vsn)</p> <p>2) Doing Top3, I chose not to impute any further the missing peptide intensities</p> <p>3) Taking the protein groups identified by MaxQuant and reported in the proteinGroup file, the protein intensities are calculated as the mean of the three most intense peptide of the leading razor protein.</p> <p>4) If no protein is found in a sample, the reported intensity is zero</p> <p>5) Differential analysis using the empirical Bayes statistics from the bioconductor limma packed is performed with the false discovery rate set at 0.01. Most proteins showing significant difference are only in SPO11.</p> <p>MaxQuant proteinGroups and evidence file are joined as sheets in the Mass Spec Spo11_raw.xlsx. The first sheet, "Differential Analysis", marks the proteins significantly different in SPO versus CTR (first column), under the test condition described above. The next 6 columns are the Top3 intensities in each sample. You may also want to ignore proteins with Q>0 (column BL in the file).</p> <p> </p> <p> </p>
Data from: Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli
Background: In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Methods: Specific peaks in the outbreak strain's spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Results: Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. Conclusions: MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.
Data from: A proteomic method to extract, concentrate, digest, and enrich peptides from fossils with colored (humic) substances for mass spectrometry analyses
Humic substances are break-down products of decaying organic matter that co-extract with proteins from fossils. These substances are difficult to separate from proteins in solution, and interfere with analyses of fossil proteomes. We introduce a method combining multiple recent advances in extraction protocols to both concentrate proteins from fossil specimens with high humic content, and remove humics, producing clean samples easily analyzed by mass spectrometry (MS). This method includes: 1) a non-demineralizing extraction buffer that eliminates protein loss during the demineralization step in routine methods; 2) filter-aided sample preparation (FASP) of peptides, which concentrates and digests extracts in one filter, allowing the separation of large humics after digestion; 3) centrifugal stage-tipping, which further clarifies and concentrates samples in a uniform process performed simultaneously on multiple samples. We apply this method to a moa fossil (~800¬–1000 yr) dark with humic content, generating colorless samples and enabling the detection of more proteins with greater sequence coverage than previous MS analyses on this same specimen. This workflow allows analyses of low-abundance proteins in fossils containing humics, and thus may widen the range of extinct organisms and regions of their proteomes we can explore with MS.
Mass spectrometry data of Chalmydomonas reinhardtii central pair mutants
<p>The following data includes the mass spectrometry results from 5 different strains of Chlamydomonas reinhardtii. The first strain is CC-124 or more commonly referred to as the wild type strain. The second strain is a mutant that lacks the central pair <em>pf15</em>. Other central pair mutants are <em>pf16</em>, <em>pf6</em> and <em>cpc1</em>.</p> <p>All strains were cultured under identical conditions and the doublet microtubules were purified and treated twice with NaCl before mass spectrometry. Biological triplicates were performed on each strain for mass spectrometry.</p>
Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics - Data Supplement
<p>This the is Data Supplement for the article "Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics" submitted to the Journal of Proteomics 2015.</p>
mzML mass spectrometry and imzML mass spectrometry imaging test data
<p>The repository contains three mzML and four imzML mass spectrometry datasets, </p><p>The mzML data are compiled in a <strong>single directory 'mzML' and zipped</strong>:</p><ul><li><strong>Col_1.mzML </strong>is a liquid chromatography (LC) ESI MS dataset from an Arabidopsis extraction published in: Sotelo-Silveira, M., Chauvin, A.-L., Marsch-Martínez, N., Winkler, R. & De Folter, S. Metabolic fingerprinting of Arabidopsis thaliana accessions. Frontiers in Plant Science 6, 1–13 (2015). <a href="https://doi.org/10.3389/fpls.2015.00365">https://doi.org/10.3389/fpls.2015.00365</a>.</li><li><strong>Cytochrome_C.mzML</strong> is an electrospray mass spectrometry (ESI MS) dataset of Cytochrome C. The data were discussed in: Winkler, R. ESIprot: a universal tool for charge state determination and molecular weight calculation of proteins from electrospray ionization mass spectrometry data. Rapid Communications in Mass Spectrometry 24, 285- 294 (2010). <a href="https://doi.org/10.1002/rcm.4384">https://doi.org/10.1002/rcm.4384</a>.</li><li><strong>T9_A1.mzML </strong>is a low-temperature plasma (LTP) MS dataset of the interaction between Arabidopsis and Trichoderma, published in 1. Torres-Ortega, R. et al. In Vivo Low-Temperature Plasma Ionization Mass Spectrometry (LTP-MS) Reveals Regulation of 6-Pentyl-2H-Pyran-2-One (6-PP) as a Physiological Variable during Plant-Fungal Interaction. Metabolites 12, 1231 (2022). <a href="https://doi.org/10.3390/metabo12121231">https://doi.org/10.3390/metabo12121231</a>.</li></ul><p>The imzML mass spectrometry imaging data are zipped individually:</p><ul><li><strong>imzML_AP_SMALDI.zip </strong>contains an AP-SMALDI mass spectrometry imaging data set of mouse urinary bladder slides, published by Römpp A, Guenther S, Schober Y, Schulz O, Takats Z, Kummer W, Spengler B., ProteomeXchange dataset PXD001283. 2014., and available from <a href="https://www.ebi.ac.uk/pride/archive/projects/PXD001283">https://www.ebi.ac.uk/pride/archive/projects/PXD001283</a>; Publication: Römpp A, Guenther S, Schober Y, Schulz O, Takats Z, Kummer W, Spengler B; Histology by mass spectrometry: label-free tissue characterization obtained from high-accuracy bioanalytical imaging., Angew Chem Int Ed Engl, 49, 22, 3834-8 (2014). <a href="https://doi.org/10.1002/anie.200905559">https://doi.org/10.1002/anie.200905559</a>, PubMed: 20397170. </li><li><strong>imzML_DESI.zip </strong>is a DESI mass spectrometry imaging data set of human colorectal cancer tissue by Oetjen J, Veselkov K, Watrous J, McKenzie JS, Becker M, Hauberg-Lotte L, Kobarg JH, Strittmatter N, Mróz AK, Hoffmann F, Trede D, Palmer A, Schiffler S, Steinhorst K, Aichler M, Goldin R, Guntinas-Lichius O, von Eggeling F, Thiele H, Maedler K, Walch A, Maass P, Dorrestein PC, Takats Z, Alexandrov T. 2015. Benchmark datasets for 3D MALDI-and DESI-imaging mass spectrometry. GigaScience 4(1):2105 <a href="https://doi.org/10.1186/s13742-015-0059-4">https://doi.org/10.1186/s13742-015-0059-4</a>.</li><li><strong>imzML_LA-ESI.zip</strong> is an LA-ESI mass spectrometry imaging data set of an <i>Arabidopsis thaliana</i> leaf by Zheng, Z., Bartels, B., & Svatoš, A. (2020). Laser Ablation Electrospray Ionization Mass Spectrometry Imaging (LAESI MSI) of Arabidopsis thaliana leaf [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3678473">https://doi.org/10.5281/zenodo.3678473</a>. </li><li>imzML_LTP.zip was generated by low-temperature plasma ionization ambient mass spectrometry imaging of a chili fruit, published by Maldonado-Torres M, López-Hernández Jé F, Jiménez-Sandoval P, Winkler R. 2014. Plug and play' assembly of a low-temperature plasma ionization mass spectrometry imaging (LTP-MSI) system. Journal of Proteomics 102C:60–65 <a href="https://doi.org/10.1016/j.jprot.2014.03.003">https://doi.org/10.1016/j.jprot.2014.03.003</a>; Mauricio Maldonado-Torres, José Fabricio López-Hernández, Pedro Jiménez-Sandoval, & Robert Winkler. (2017). Low-temperature plasma mass spectrometry imaging (LTP-MSI) of Chili pepper [Data set]. In Journal of proteomics (Vol. 102, pp. 60–65). Zenodo. <a href="https://doi.org/10.5281/zenodo.484496">https://doi.org/10.5281/zenodo.484496</a>.</li></ul><p>All these datasets are publicly available from different repositories; however, If you reuse them, <strong>please attribute the original authors!</strong></p>
Raw mass spectrometry data associated to Remy et al 2023
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Raw data for the submitted manuscript entitled "Novel strategies for the determination of plastic additives derived from agricultural plastics in soil using ultrahigh-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS)"
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ScienceDex guides
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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.