Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis. See more information about the full DIMSpec code base - as well as these data for demonstration purposes - at GitHub (https://github.com/usnistgov/dimspec) or view the full User Guide for DIMSpec (https://pages.nist.gov/dimspec/docs).Files of most interest contained here include the database file itself (dimspec_nist_pfas.sqlite) as well as an entity relationship diagram (ERD.png) and data dictionary (DIMSpec for PFAS_1.0.1.20230615_data_dictionary.json) to elucidate the database structure and assist in interpretation and use.

A multistage tandem mass spectral database using a variety of structurally defined glycans. It provides tools for glycomics research that enable users to identify glycans by spectral matching. The database stores MS2, MS3, and MS4 spectra of N-and O-linked glycans, and glycolipid glycans as well as the partial structures of these glycans.

Measurement data of aboveground litterfall and littermass and litter carbon, nitrogen, and nutrient concentrations were extracted from 685 original literature sources and compiled into a comprehensive database to support the analysis of global patterns of carbon and nutrients in litterfall and litter pools. Data are included from sources dating from 1827 to 1997. The reported data include the literature reference, general site information (description, latitude, longitude, and elevation), site climate data (mean annual temperature and precipitation), site vegetation characteristics (management, stand age, ecosystem and vegetation-type codes), annual quantities of litterfall (by class, kg m-2 yr-1), litter pool mass (by class and litter layer, kg m-2), and concentrations of nitrogen (N), phosphorus (P), and base cations for the litterfall (g m-2 yr-1) and litter pool components (g m-2). The investigators intent was to compile a comprehensive data set of individual direct field measurements as reported by researchers. While the primary emphasis was on acquiring C data, measurements of N, P, and base cations were also obtained, although the database is sparse for elements other than C and N. Each of the 1,497 records in the database represents a measurement site. Replicate measurements were averaged according to conventions described in Section 5 and recorded for each site in the database. The sites were at 575 different locations.

January 2026

Measurement data of aboveground litterfall and littermass and litter carbon, nitrogen, and nutrient concentrations were extracted from 685 original literature sources and compiled into a comprehensive database to support the analysis of global patterns of carbon and nutrients in litterfall and litter pools. Data are included from sources dating from 1827 to 1997. The reported data include the literature reference, general site information (description, latitude, longitude, and elevation), site climate data (mean annual temperature and precipitation), site vegetation characteristics (management, stand age, ecosystem and vegetation-type codes), annual quantities of litterfall (by class, kg m-2 yr-1), litter pool mass (by class and litter layer, kg m-2), and concentrations of nitrogen (N), phosphorus (P), and base cations for the litterfall (g m-2 yr-1) and litter pool components (g m-2). The investigators intent was to compile a comprehensive data set of individual direct field measurements as reported by researchers. While the primary emphasis was on acquiring C data, measurements of N, P, and base cations were also obtained, although the database is sparse for elements other than C and N. Each of the 1,497 records in the database represents a measurement site. Replicate measurements were averaged according to conventions described in Section 5 and recorded for each site in the database. The sites were at 575 different locations.

(Version 20230306)

Version 4 (20230306) of the RKI MALDI-ToF mass spectra database is the third update of the original database (version 20161027, https://doi.org/10.5281/zenodo.163517). The RKI Database v.4 now contains a total of 11055 MALDI-ToF mass spectra from 1599 microbial strains of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as Bacillus anthracis, Brucella melitensis, Yersinia pestis, Burkholderia mallei / pseudomallei and Francisella tularensis as well as a selection of spectra of their close and distant relatives. The database can be used as a reference for the diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-ToF MS-based microbial identification. The spectral data are provided as a zip archive (zenodo db 230306.zip) containing the original mass spectra in their native data format (Bruker Daltonics). Please refer to the pdf file (230306-ZENODO-Metadata.pdf) for information on cultivation conditions, sample preparation and details of the spectra acquisition. Please do not try to print this document (>1600 pages!).

Version 20230306 of the RKI database contains for the first time a file in btmsp format (230306_v4_RKI_DB_BSL3.btmsp). This file was generated using the MALDI Biotyper software (Bruker Daltonics) and contains a total of 1599 main spectra from the BSL-3 database in the proprietary data format of the MALDI Biotyper software. *.btmsp files can be imported and used for identification with this software solution. Note that the btmsp file available in database version 4 is broken and cannot be imported. Please refer to updated database versions (4.1, or 4.2) to download valid btmsp files.

The pkf files (230306_ZENODO_30Peaks_0.75.pkf, 230306_ZENODO_45Peaks_0.75.pkf) represent two versions of the MS peak list data in a Matlab compatible format. The latter data can be imported into MicrobeMS, a free Matlab-based software solution developed at the RKI. MicrobeMS can be used for the identification of microorganisms by MALDI-ToF MS and is available at https://wiki-ms.microbe-ms.com.

The RKI mass spectrometry database is updated regularly.

The author would like to thank the following individuals for providing microbial strains and species or mass spectra thereof. Without their help, this work would not have been possible.

Wolfgang Beyer - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany

Guido Werner - Robert Koch-Institute, Nosocomial Pathogens and Antibiotic Resistances (FG13), Wernigerode, Germany

Alejandra Bosch - CINDEFI, CONICET-CCT La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina

Michal Drevinek - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic

Roland Grunow, Daniela Jacob, Silke Klee, Susann Dupke and Holger Scholz - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany

Jörg Rau - Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany

Jens Jacob - Robert Koch-Institute, Hospital Hygiene, Infection Prevention and Control (FG14), Berlin, Germany

Martin Mielke - Robert Koch-Institute, Department 1 - Infectious Diseases, Berlin, Germany

Monika Ehling-Schulz - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria

Armand Paauw - Department of Medical Microbiology, CBRN protection, Universitair Medisch Centrum Utrecht, TNO, Rijswijk, The Netherlands

Herbert Tomaso – Friedrich-Löffler-Institut (FLI), Federal Research Institute for Animal Health, Jena, Germany

Gabriel Karner - Karner Düngerproduktion GmbH, Research & Development, Neulengbach, Austria

Rainer Borriss - Institute of Marine Biotechnology e.V. (IMaB), Greifswald, Germany

Le Thi Thanh Tam - Division of Plant Pathology and Phyto-Immunology, Plant Protection Research Institute, Hanoi, Socialist Republic of Vietnam

Xuewen Gao - College of Plant Protection, Nanjing Agricultural University, Key Laboratory of Integrated Management of Crop Diseases and Pests, Nanjing, People’s Republic of China

Comprehensive list containing 73 verified Database management company businesses in Massachusetts, United States with lastest contact information, ratings, reviews, and location data.

This data represents processed data from chemical ionization time of flight mass spectrometry instrument used to generate each figure in the manuscript. A data dictionary is included in the dataset. This dataset is associated with the following publication: Mattila, J., J. Krug, W. Roberson, R. Burnette, S. McDonald, P. Virtaranta, J. Offenberg, and W. Linak. Characterizing volatile emissions and combustion by-products from aqueous film-forming foams using online chemical ionization mass spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 0, (2024).

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF). For users on Windows operating systems, the .SDF format library can be converted to NIST MS Search format using Lib2NIST and then explored using NIST MS Search v2.4 for general mass spectral analysis. These software tools can be downloaded at https://chemdata.nist.gov. The database is now (09-28-2021) also provided in R data format (.RDS) for use with the R programming language. This database, also commonly referred to as a library, is one in a series of high-quality mass spectral libraries/databases produced by NIST (see NIST SRD 1a, https://dx.doi.org/10.18434/T4H594).

The Mass Data Migration Service market is booming, projected to reach $50 billion by 2033 with an 18% CAGR. Discover key trends, drivers, and restraints shaping this rapidly expanding sector, including cloud migration, data analytics, and regulatory compliance. Learn about leading companies and regional market shares.

No description is available. Visit https://dataone.org/datasets/farshid25.54.1 for complete metadata about this dataset.

The NIST Chemistry WebBook provides users with easy access to chemical and physical property data for chemical species through the internet. The data provided in the site are from collections maintained by the NIST Standard Reference Data Program and outside contributors. Data in the WebBook system are organized by chemical species. The WebBook system allows users to search for chemical species by various means. Once the desired species has been identified, the system will display data for the species. Data include thermochemical properties of species and reactions, thermophysical properties of species, and optical, electronic and mass spectra.

March 2024

This collection of asteroid masses and densities was compiled from the published literature by Jim Baer, Steve Chesley, and Dan Britt. Size and shape information are included as well to show the source of the tabulated bulk density. This is the version of the compilation as of April 18, 2012.

A database of proteins and RNAs that have been identified in various purified splicing complexes. Various names, orthologs and gene identifiers of spliceosome proteins have been cataloged to navigate the complex nomenclature of spliceosome proteins. Links to gene and protein records are also provided for the spliceosome components in other databases. To navigate spliceosome assembly dynamics, tools were created to compare the association of spliceosome proteins with complexes that form at specific stages of spliceosome assembly based on a compendium of mass spectrometry experiments that identified proteins in purified splicing complexes.

We have collected seed mass data for almost 13,000 species (angiosperms and gymnosperms) from all around the world. We have constructed a phylogeny for these species, and are using this, plus data on plant growth form, seed dispersal syndrome, vegetation type, net primary productivity, temperature, precipitation and leaf area index to look at factors that have influenced the evolution of seed size.

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for “viewing” the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user’s choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of “viewing” the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide “sequences” for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/.

Additional file 7: Table S6. Identification of new isolates from the same mice fecal samples.

Cross-linking/mass spectrometry has undergone a maturation process akin to standard proteomics by adapting key methods such as false discovery rate control and quantification. A poorly evaluated search setting in proteomics is the consideration of multiple (lighter) alternative values for the monoisotopic precursor mass to compensate for possible misassignments of the monoisotopic peak. Here, we show that monoisotopic peak assignment is a major weakness of current data handling approaches in cross-linking. Cross-linked peptides often have high precursor masses, which reduces the presence of the monoisotopic peak in the isotope envelope. Paired with generally low peak intensity, this generates a challenge that may not be completely solvable by precursor mass assignment routines. We therefore took an alternative route by ‘”in-search assignment of the monoisotopic peak” in the cross-link database search tool Xi (Xi-MPA), which considers multiple precursor masses during database search. We compare and evaluate the performance of established preprocessing workflows that partly correct the monoisotopic peak and Xi-MPA on three publicly available data sets. Xi-MPA always delivered the highest number of identifications with ∼2 to 4-fold increase of PSMs without compromising identification accuracy as determined by FDR estimation and comparison to crystallographic models.