MassBank: a public repository for sharing mass spectral data for life sciences.

By Hisayuki Horai, Masanori Arita, Shigehiko Kanaya, Yoshito Nihei, Tasuku Ikeda, Kazuhiro Suwa, Y. Ojima, Kenichi Tanaka, Satoshi Tanaka, K. Aoshima and 24 more. Journal of Mass Spectrometry, 2010

2,281 citations recorded by the source corpus.

MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/5289463e90a350b57a5f84190c456d8c38d86368

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Citations in the corpus

RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database. (2012, methodology): “The records were formatted using MassBank Record (Horai et al., 2010), which can accept MS/MS data as well as its metadata (summary, chemical, analytical, spectral and outer database links).”
MetFrag relaunched: incorporating strategies beyond in silico fragmentation (2016, methodology): “The MetFusion [19] approach takes advantage of the availability of spectral data for some compounds and performs a combined query of both MetFrag and MassBank [20], such that the scores of candidates with high chemical similarity to high-scoring reference spectra are increased.”
Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics (2018, background): “The MassBank database (http://massbank.jp) is one of the most successful examples, with a wide user base and contributors from many different countries [52].”
HMDB 3.0—The Human Metabolome Database in 2013 (2012, methodology): “In particular, hundreds of additional reference MS and NMR spectra were collected, assigned and/or annotated by the curation team, whereas hundreds of additional annotated/assigned MS and NMR reference spectra were obtained from the BioMagResBank (12), METLIN (5) and MassBank (13).”
Untargeted metabolomics strategies – Challenges and Emerging Directions (2016, background): “com), METLIN [15], Human Metabolome DataBase (HMDB) [16], MassBank [17], mzCloud (https://www.”
Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis (2015, neutral): “MassBank MS/MS [42–44] – 3,350 3,350”
metaX: a flexible and comprehensive software for processing metabolomics data (2017, methodology): “Currently, metaX provides a function for metabolite identification based on the Human Metabolome Data-base (HMDB) [31], KEGG [32, 33], MassBank [34], Pub-Chem [35], LIPID MAPS [36], MetaCyc [37] and PlantCyc (www.plantcyc.org).”
Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics (2020, methodology): “Future work will also implement workflows in Skyline to support fragmentation libraries of small molecules, such as Metlin (http://metlin.scripps.edu/) 47, 48 , MassBank 49 , the Human Metabolome Database (HMDB, http://www.hmdb.ca/) 50, 51 and the National Institute of Standards and Technology Datab”
CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra (2014, methodology): “The Human Metabalome Database (14), Metlin (4) and MassBank (16) all have search functionality that query these databases for likely molecules matching an input MS / MS spectrum.”