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103 results for “MALDI”
A Combined approach of MALDI-TOF Mass Spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs.
<p>The spectra were provided as unprocessed raw data in the manufacturers data format (Bruker), as labelled two zip archives with SARS CoV 2 positives and negative, according to the reviewer's recommendation.</p> <p>This information belongs to the publication (in review in <em>Journal of Virological Methods</em>)<br> "A Combined approach of MALDI-TOF Mass Spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs"<br> All the information belongs to the National Reference Institute, INEI-ANLIS DR CARLOS G MALBRAN, BUENOS AIRES, ARGENTINA.</p>
MALDI-TOF-MS archaeological spectra and for African bovid collagen for Zooarchaeology by Mass Spectrometry (ZooMS) from Zambia
<p>The MALDI data for archaeological samples from Zambia. The spectra are all in the folder in .mzml format. The samples are labeled the same as in the corresponding manuscript. The modern African bovid spectra that were used to determine markers can be found at Zenodo doi:10.5281/zenodo.3964709.</p>
Cross-linked Mass Spectrometry (MALDI) data of GR C3 NTD and TSG101cc
<p>The zip file contains three folders from three separate datasets. The proteins were cross-linked with DST and then run on SDS-PAGE to separate unlinked protein. Bands were cut from the gels and then proteolyses overnight before conducting MS. Most of the datasets were collected using trypsin to produce protein fragments or in one case trypsin + chymotrypsin. Each folder contains a large number of control samples including: blank portions of the gel, uncross-linked protein samples, cross-linked GR without TSG101, cross-linked TSG101 without GR (four different bands because of much self-cross-linking). The files were hand curated for analysis.</p>
Data from: Comparison of rapid biodiversity assessment of meiobenthos using MALDI-TOF MS and metabarcoding
<p>Nowadays, most biodiversity assessments involving meiofauna are mainly carried out using very time-consuming, specimen-wise morphological identifications, which demands comprehensive taxonomic knowledge. Animals have to be examined for minor differences of setae compositions, mouthpart morphology or number of segments for various extremities. DNA-based methods such as metabarcoding as well as recently emerged rapid analyses using MALDI-TOF mass spectrometry to identify specimens based on a proteome fingerprint could vastly accelerate the process of specimen identification in biodiversity assessments. However, these techniques depend on reference libraries to connect collected data to morphologically described species. In this study the success rate of both approaches have been tested based on reference libraries constructed using part of the samples from a new study area to identify unknown samples. Using MALDI-TOF MS we found, that species which do not exist in an incomplete mass spectra reference library only have minor impact on the results, when employing a post hoc test for Random Forest classifications. This test reveals specimens that demand morphological re-examination for the final species assignment. Metabarcoding however strongly demands a rich reference library to provide correct MOTU assessments in congruence with morphological determination. Nevertheless, with a complete library and a suitable data transformation [herein log(x + 1)], the number of reads per MOTU reflects relative species abundances in metabarcoding inference. The results of this study facilitate specimen identification by using MALDI-TOF MS, which is incomparably cheap for specimen-by specimen identification, but when it comes to sample-wise analyses, metabarcoding outperforms other techniques by far.</p>
A MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch-Institute (RKI)
<p><em>(Version 20161027) </em></p> <p><strong><em>Edit #1 (May 23, 2017): New database version (v.2 - 20170523) - available</em>: </strong> <a href="https://doi.org/10.5281/zenodo.582602">10.5281/zenodo.582602</a></p> <p><strong><em>Edit #2 (Nov 30, 2018): New database version (v.3 - 20181130) - available</em>: </strong> <a href="https://doi.org/10.5281/zenodo.1880975">10.5281/zenodo.1880975</a></p> <p><strong><em>Edit #3 (Mar 06, 2023): New database version (v.4.2 - 20230306) - available</em>: </strong> <a href="https://zenodo.org/records/14562231">10.5281/zenodo.7702375</a></p> <p> </p> <p>The Robert Koch-Institute (RKI) database of microbial MALDI-TOF mass spectra contains mass spectral entries from highly pathogenic (biosafety level 3, BSL-3) bacteria such as <em>Bacillus anthracis</em>, <em>Yersinia pestis</em>, <em>Burkholderia mallei</em>, <em>Burkholderia pseudomallei</em> and <em>Francisella tularensis</em> as well as a selection of spectra from their close and more distant relatives. The RKI mass spectral database can be used as a reference for the diagnostics of BSL-3 bacteria using proprietary and free software packages for MALDI-TOF MS-based microbial identification. The database itself is distributed as a zip archive that contains the original mass spectra in its native data format (Bruker Daltonics). Please refer to the pdf file (161027-ZENODO-Metadata.pdf) to obtain information on the metadata of the spectra. Do not try to print this document (~1000 pages!)</p> <p>The pkf-file (161027_zenodo_Peaklist_(30Peaks1,6).pkf ) contains <em>so-called</em> database spectra in a Matlab compatible format. The latter data file can be imported into MicrobeMS, a Matlab-based free-of-charge software solution developed at the RKI. MicrobeMS is available from http://www.microbe-ms.com.</p> <p>For the future it is intended to update the RKI database of MALDI-TOF mass spectra on a regular basis.</p> <p>The author's grateful thanks are given to the following persons for providing microbial strains and species. Without their help this work would not be possible.</p> <ul> <li>Wolfgang Beyer - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany</li> <li>Guido Werner - Robert Koch-Institute, <em> Nosocomial Pathogens and Antibiotic Resistances</em> (FG13), Wernigerode, Germany</li> <li>Alejandra Bosch - CINDEFI, CONICET-CCT La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina</li> <li>Michal Drevinek - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic</li> <li>Roland Grunow - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li>Daniela Jacob - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li>Silke Klee - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li>Jörg Rau - Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany</li> <li>Jens Jacob - Robert Koch-Institute, <em>Hospital Hygiene, Infection Prevention and Control </em>(FG14), Berlin, Germany</li> <li>Martin Mielke - Robert Koch-Institute, <em>Department 1 - Infectious Diseases</em>, Berlin, Germany</li> <li>Monika Ehling-Schulz - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria</li> </ul> <p> </p>
Version 2 (20170523) of the MALDI-TOF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch-Institute (RKI)
<p><em>(Version </em>20170523<em>) </em></p> <p><strong><em>Edit #1 (Nov 30, 2018): New database version (v.3 - 20181130) - available</em>: </strong> <a href="https://doi.org/10.5281/zenodo.1880975">10.5281/zenodo.1880975</a></p> <p><strong><em>Edit #2 (Mar 06, 2023): New database version (v.4.2 - 20230306) - available</em>: </strong> <a href="https://zenodo.org/records/14562231">10.5281/zenodo.7702375</a></p> <p>Version 2 (20170523) of the RKI’s MALDI-TOF mass spectral database is an update of the original database (version 20161027, https://doi.org/10.5281/zenodo.163517). The RKI database contains mass spectral entries from highly pathogenic (biosafety level 3, BSL-3) bacteria such as <em>Bacillus anthracis</em>, <em>Yersinia pestis</em>, <em>Burkholderia mallei</em>, <em>Burkholderia pseudomallei</em> and <em>Francisella tularensis</em> as well as a selection of spectra from their close and more distant relatives. The database can be used as a reference for the diagnostics of BSL-3 bacteria using proprietary and free software packages for MALDI-TOF MS-based microbial identification. Spectral data are distributed as a 7-zip archive that contains the original mass spectra in its native data format (Bruker Daltonics). Please refer to the pdf file (170523-ZENODO-Metadata.pdf) to obtain information on the metadata of the spectra. Do not try to print this document (~1100 pages!)</p> <p>The pkf-file (170523_ZENODO_Peaklist_30Peaks_1.6.pkf) contains the MS peak list data in a Matlab compatible format. The latter data file can be imported into MicrobeMS, a Matlab-based free-of-charge software solution developed at RKI. MicrobeMS is available from http://www.microbe-ms.com.</p> <p>The RKI mass spectral database will be updated on a regular basis.</p> <p>The author's grateful thanks are given to the following persons for providing microbial strains and species. Without their help this work would not be possible.</p> <ul> <li><strong>Wolfgang Beyer</strong> - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany</li> <li><strong>Guido Werner</strong> - Robert Koch-Institute, <em>Nosocomial Pathogens and Antibiotic Resistances</em> (FG13), Wernigerode, Germany</li> <li><strong>Alejandra Bosch</strong> - <em>CINDEFI, CONICET-CCT</em> La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina</li> <li><strong>Michal Drevinek</strong> - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic</li> <li><strong>Roland Grunow</strong> - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li><strong>Daniela Jacob</strong> - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li><strong>Silke Klee</strong> - Robert Koch-Institute, <em>Highly Pathogenic Microorganisms</em> (ZBS2), Berlin, Germany</li> <li><strong>Jörg Rau</strong> - Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany</li> <li><strong>Jens Jacob</strong> - Robert Koch-Institute, <em>Hospital Hygiene, Infection Prevention and Control </em>(FG14), Berlin, Germany</li> <li><strong>Martin Mielke</strong> - Robert Koch-Institute, <em>Department 1 - Infectious Diseases</em>, Berlin, Germany</li> <li><strong>Monika Ehling-Schulz</strong> - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria</li> <li><strong>Armand Paauw</strong> - Department of Medical Microbiology, CBRN protection, Universitair Medisch Centrum Utrecht, TNO, Rijswijk, The Netherlands</li> </ul>
Design and high-throughput implementation of MALDI-TOF/MS-based assays for Parkin E3 ligase activity
<p><strong>Summary</strong></p> <p><span>Parkinson’s disease (PD) is a progressive neurological disorder that manifests clinically as alterations in movement as well as multiple non-motor symptoms including but not limited to cognitive and autonomic abnormalities. Loss-of-function mutations in the gene encoding the ubiquitin E3 ligase Parkin are causal for familial and juvenile PD. Among several therapeutic approaches being explored to treat or improve PD patient’s prognosis, the use of small molecules able to reinstate or boost Parkin activity represents a potential pharmacological treatment strategy. A major barrier is the lack of high throughput platforms for the robust and accurate quantification of Parkin activity <em>in vitro</em>. Here we present two different and complementary Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF/MS) based approaches for the quantification of Parkin E3 ligase activity<em> in vitro</em>. Both approaches are scalable for high-throughput primary screening to facilitate the identification of Parkin modulators.</span></p>
MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D | MALDI Data
<p>This repository contains MALDI data related to the Ma et al. study "<strong>MetaVision3D: Automated Framework for the Generation of Spatial Metabolome Atlas in 3D</strong>". Processed MALDI pixel-by-pixel .csv files for both metabolomics and lipidomics for two Wild-type samples, one 5xFAD sample and one GAA sample. If you use this dataset in your research, please consider citing the above study.</p> <p>The content of the files are:<br>wt.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type sample.</p> <p>5x.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for 5xFAD sample.</p> <p>gaa.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for GAA sample.</p> <p>wt2.zip - pixel-by-pixel .csv files of metabolomics and lipidomics for wild-type2 sample.</p>
DRIAMS: Database of Resistance Information on Antimicrobials and MALDI-TOF Mass Spectra
<p>Early administration of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from MALDI-TOF mass spectra profiles of clinical samples. We trained calibrated classifiers on a newly-created publicly available database of mass spectra profiles from clinically most relevant isolates with linked antimicrobial susceptibility phenotypes. The dataset combines more than 300,000 mass spectra with more than 750,000 antimicrobial resistance phenotypes from four medical institutions. Validation against a panel of clinically important pathogens, including Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae, resulting in AUROC values of 0.80, 0.74, and 0.74 respectively, demonstrated the potential of using machine learning to substantially accelerate antimicrobial resistance determination and change of clinical management. Furthermore, a retrospective clinical case study found that implementation of this approach would have resulted in a beneficial change in the clinical treatment in 88% (8/9) of cases. MALDI-TOF mass spectra based machine learning may thus be an important new tool for treatment optimization and antibiotic stewardship.</p>
MALDI-TOF MS data: Species delimitation of Hexacorallia and Octocorallia around Iceland using nuclear and mitochondrial DNA and proteome fingerprinting
<p>Cold-water corals build up reef structures or coral gardens and play an important role for many organisms in the deep sea. Climate change, deep-sea mining, and bottom trawling are severely compromising these ecosystems, making it all the more important to document the diversity, distribution, and impacts on corals. This goes hand in hand with species identification, which is morphologically and genetically challenging for Hexa- and Octocorallia. Morphological variation and slowly evolving molecular markers both contribute to the difficulty of species identification. In this study, a fast and cheap species delimitation tool for Octocorallia and Scleractinia of the Northeast Atlantic was tested based on 49 specimens. Two nuclear markers (ITS2 and 28S rDNA) and two mitochondrial markers (COI and mtMutS) were sequenced. The sequences formed the basis of a reference library for comparison to the results of species delimitation based on proteomic analysis using the MALDI-TOF MS method. The genetic methods were able to distinguish 17 of 18 presumed species. The MALDI-TOF MS method was able to distinguish 7 species. Species that could not be distinguished from one another still achieved good signals but were not represented by enough specimens for comparison. Therefore, it is predicted that with an extensive reference library of proteome spectra for Scleractinia and Octocorallia, MALDI-TOF MS may provide a rapid and cost-effective alternative for species discrimination in corals.</p>
Direct prediction for carbapenemase-producing and colistin-resistant Klebsiella pneumoniae isolates from routine MALDI-TOF mass spectrum using machine learning
<p>The emergence of carbapenem-nonsusceptible K. pneumoniae (CnSKP) leads a serious threat to patient survival and colistin resistance makes the treatment of CnSKP more difficultly. To make treatment strategy properly and quickly, we aimed to develop a rapid prediction method for CnSKP and colistin-resistant K. pneumoniae (ColRKP) based on the spectra of routine matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI–TOF MS). The machine learning (ML) model for differentiating CnSKP and carbapenem-susceptible K. pneumoniae (CSKP) showed accuracy of 0.8869 and AUC of 0.9551; the model for ColRKP and colistin-intermediate K. pneumoniae (ColIKP) showed accuracy of 0.8361 and the AUC of 0.8447.</p>
MALDI-MS raw files of primary human lung cancer samples, lung cancer patient derived xenografts and lung cancer mouse models
<p>Human primary lung cancer samples, patient derived lung cancer xenografts and lung tumors from the TetO-KRASG12D mouse model were analyzed using MALDI-MS. We determined the spatial distribution and relative abundance of lipids of interest. </p>
Rapid pathogen identification in aqueous humor samples by combining Fc-MBL@Fe3O4 enrichment and MALDI-TOF MS profiling
<p>Prompt clinical diagnosis and antimicrobial therapy are key to managing infective endophthalmitis. The small volume of aqueous humor, low bacterial counts, and empirical medication by physicians make existing diagnostic methods time-consuming and imprecise. Here, we investigated the feasibility of combining Fc-MBL@Fe3O4 enrichment with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling to identify pathogens in aqueous humor. Aqueous humor aspirated from freshly enucleated porcine eyes was inoculated with different inocula of <em>Staphylococcus aureus</em> (<em>S. aureus</em>), <em>Staphylococcus </em><em>epidermidis</em> (<em>S. epidermidis</em>), and <em>Klebsiella pneumoniae</em> (<em>K. pneumoniae</em>). We performed identification directly in aqueous humor samples and after short-term culture of micro-LB broth. Aqueous humor endophthalmitis samples were enriched with Fc-MBL@Fe3O4 and analyzed with MALDI-TOF MS. The identification time and minimum bacterial concentration required for identification were determined. The enrichment efficiency of Fc-MBL@Fe3O4 for different bacteria was > (87.5±5.0)%. The objects of direct identification include live bacteria and bacteria treated with antibiotics, which can be completed within 1.5 hours. The minimum number of bacteria needed for positive identification was 2.20×10<sup>6 </sup>CFU. For micro-LB broth culture, the identification of bacteria can be completed within 6.5-9.5 h for aqueous humor samples with an initial bacterial count of tens to hundreds.</p>
MALDI imaging data uploaded to Metaspace (2017)
<p>MALDI imaging data uploaded to Metaspace http://annotate.metaspace2020.eu/#/datasets from our lab. All metabolite annotations can be browsed.</p>
Training dataset: MALDI imaging of N-glycans in murine kidney sections
<p>The files provided here are all adopted from the <a href="http://www.ebi.ac.uk/pride/archive/projects/PXD009808">PRIDE PXD009808 datasets</a> and the corresponding publication: Ove J. R. Gustafsson, Matthew T. Briggs, Mark R. Condina, Lyron J. Winderbaum, Matthias Pelzing, Shaun R. McColl, Arun V. Everest-Dass, Nicolle H. Packer, Peter Hoffmann. “MALDI imaging mass spectrometry of N-linked glycans on formalin-fixed paraffin-embedded murine kidney.” Analytical and Bioanalytical Chemistry (2015) 407: 2127. <a href="https://doi.org/10.1007/s00216-014-8293-7">https://doi.org/10.1007/s00216-014-8293-7</a></p> <p><br> Three 6µm sections of formalin-fixed paraffin-embedded murine kidney tissue specimens were prepared for MALDI imaging. To release N-linked glycans, PNGase F was printed onto two kidney sections. In the third section one area was printed with buffer to serve as a control and another area was covered with N-glycan calibrants (Gustafsson et al., Figure 4 a-c). 2,5-DHB matrix was sprayed onto the tissue sections and MALDI imaging was performed with 100 µm spatial resolution using a MALDI-TOF/TOF instrument.</p> <p><br> We processed the original imzML files to make them concise but meaningful as training data sets in the Galaxy training network (https://galaxyproject.github.io/training-material/).<br> We reduced the m/z range to 1250 – 2310 and resampled the m/z values with a step size of 0.1. The main part of the training is based on the control and first treated kidney file for which we selected representative pixels to further decrease file size (files: ‘control’, ‘treated1’). To test the results on the complete dataset we also provide a file in which both treated kidney sections, the control and the calibrant files are combined after decreasing and resampling the m/z range as described above. The combined file was normalized to the total ion current (TIC) (file: ‘all_files’). All processing steps were performed on<a href="http://https://usegalaxy.eu"> https://usegalaxy.eu</a> with the tools ‘MSI filtering’, ‘MSI combine’ and ‘MSI preprocessing’ in version 1.12.1.3).<br> Additionally, the LC-MS/MS results were extracted from table S2 of the publication by Gustafsson et al. and are provided as tabular file to enable the N-glycan identification (file: 'Glycan_IDs').</p>
Database of retrosynthesis, SA-score and Ei values for AI-Design of ET MALDI matrices
Open the record for dataset details and reuse information.
MALDI imaging of mouse kidney peptides - test dataset
<p>This imzML test file is concise but meaningful as a training data set in the Galaxy training network (https://galaxyproject.github.io/training-material/).</p> <p>One 6 µm thick section of formalin-fixed paraffin-embedded mouse kidney (from 6 month old, male, C57 black 6 mice) was mounted onto an indium-tin oxide (ITO) glass slide, deparaffinized and subjected to antigen retrieval in citric acid (pH 6, 100°C, 1h). Before and after antigen retrieval the sample was washed with 10mM ammonium bicarbonate buffer. After air drying, four 1 µl spots of Bombesin (0.01 mg/ml) were placed around the tissue to control digestion.<strong> </strong>Trypsin was sprayed onto the tissue with the iMatrix Sprayer and the sample was incubated for 2 h at 50°C in a humid chamber. Internal Calibrants (Angiotensin I, Substance P, [Glu]-Fibrinopeptide B, ACTH 18-39) were mixed with α-Cyano-4-hydroxycinnamic acid (CHCA) matrix and sprayed onto the sample.</p> <p>The sample was measured with the Applied Biosystems/MDS SCIEX 4800 MALDI TOF/TOF™ Analyzer in reflector positive ion mode and a spatial resolution of 150 µm. The acquired Analyze7.5 file was loaded into Cardinal and filtered to reduce file size and decrease analysis time: Filtering was done for m/z values between 1220 and 1625 as well as pixel that represent about half of the kidney and one Bombesin digestion control spot. The data was exported in the common data format imzML.</p> <p> </p>
A comparison of minimally-invasive sampling techniques for ZooMS analysis of bone artifacts: MALDI-TOF mass spectra
<p><span></span></p> <p>Bone and antler are important raw materials for tool manufacture in many cultures, past and present. The modification of osseous features which take place during artifact manufacture frequently makes it difficult to identify either the bone element or the host animal, which can limit our understanding of the cultural, economic, and/or symbolic factors which influence raw material acquisition and use. While biomolecular approaches can provide taxonomic identifications of bone or antler artifacts, these methods are frequently destructive, raising concerns about invasive sampling of culturally-important artifacts or belongings. Collagen peptide mass fingerprinting (Zooarchaeology by Mass Spectrometry or ZooMS) can provide robust taxonomic identifications of bone and antler artifacts. While the ZooMS method commonly involves destructive subsampling, minimally-invasive sampling techniques based on the triboelectric effect have also been proposed. In this paper, we compare three previously proposed minimally-invasive sampling methods (forced bag, eraser, and polishing film) on an assemblage of 15 bone artifacts from the pre-contact site EjTa-4, a large midden complex located on Calvert Island, British Columbia, Canada. We compare the results of the minimally-invasive methods to 10 fragmentary remains sampled using the conventional destructive ZooMS method. We assess the reliability and effectiveness of these methods by comparing MALDI-TOF spectral quality, the number of diagnostic and high molecular weight peaks as well as the taxonomic resolution reached after identification. We find that coarse fiber-optic polishing films are the most effective of the minimally-invasive techniques compared in this study, and that the spectral quality produced by this minimally-invasive method was not significantly different from the conventional destructive method. Our results suggest that this minimally-invasive sampling technique for ZooMS can be successfully applied to culturally significant artifacts, providing comparable taxonomic identifications to the conventional, destructive ZooMS method.</p>
MALDI-MS dataset for use with open-source untargeted metabolomic workflow for complex biological samples
<p class="MsoNormal">Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free to-use data processing and analysis tools exist for various untargeted MS approaches, but choosing the 'correct' pipeline isn't straight-forward. This data set can be used in conjunction with a user-friendly online guide which presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide exploratory analysis in order to inform decision-making regarding costly and time-consuming downstream targeted MS approaches. The workflow provides practical advice concerning experimental design, organisation of data and downstream analysis, and offers details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/ changing methodologies and increased clarity and detail as user participation becomes more common allowing contributions and improvements to the workflow via the online repository. </p>
MALDI-TOF-MS spectra of modern South African rodents for ZooMS
<p>MALDI-TOF-MS spectra of extracted collagen from modern South African rodents. These spectra were used to develop peptide markers for Zooarchaeology by Mass Spectrometry (ZooMS). All spectra are uploaded in .mzml format.</p> <p>One sample per species was also analyzed with LC-MS/MS. This data is available at PXD040129 and were uploaded through MassIVE (MSV000091290).</p>
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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.
Annotated Behaviour and Observability Dataset (ABODe)
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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
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