{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:05:21Z","timestamp":1772690721960,"version":"3.50.1"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Science Foundation","award":["1552240"],"award-info":[{"award-number":["1552240"]}]},{"name":"National Science Foundation","award":["1723248"],"award-info":[{"award-number":["1723248"]}]},{"name":"National Science Foundation","award":["1723006"],"award-info":[{"award-number":["1723006"]}]},{"name":"National Science Foundation","award":["1723196"],"award-info":[{"award-number":["1723196"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Mass spectrometry (MS) uses mass-to-charge ratios of measured particles to decode the identities and quantities of molecules in a sample. Interpretation of raw MS depends upon data processing algorithms that render it human-interpretable. Quantitative MS workflows are complex experimental chains and it is crucial to know the performance and bias of each data processing method as they impact accuracy, coverage, and statistical significance of the result. Creation of the ground truth necessary for quantitatively evaluating MS1-aware algorithms is difficult and tedious task, and better software for creating such datasets would facilitate more extensive evaluation and improvement of MS data processing algorithms.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating MS1 ground truth. The software retains the first version\u2019s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving, and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also be used to view and explore the results of feature finding algorithms.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>JS-MS 2.0 enables faster creation and inspection of MS1 ground truth data. It is publicly available with an MIT license at github.com\/optimusmoose\/jsms.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-020-03752-7","type":"journal-article","created":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T13:03:33Z","timestamp":1600952613000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A web-based system for creating, viewing, and editing precursor mass spectrometry ground truth data"],"prefix":"10.1186","volume":"21","author":[{"given":"Jessica","family":"Henning","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1864-9110","authenticated-orcid":false,"given":"Rob","family":"Smith","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,23]]},"reference":[{"key":"3752_CR1","volume-title":"Electrospray ionization mass spectrometry: fundamentals, instrumentation, and applications","author":"RB Cole","year":"1997","unstructured":"Cole RB. 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BMC Bioinform. 2017;18(1):469.","journal-title":"BMC Bioinform."},{"issue":"1","key":"3752_CR8","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1002\/pmic.201300246","volume":"14","author":"HL R\u00f6st","year":"2014","unstructured":"R\u00f6st HL, Schmitt U, Aebersold R, Malmstr\u00f6m L. Pyopenms: a python-based interface to the OpenMS mass-spectrometry algorithm library. Proteomics. 2014;14(1):74\u20137.","journal-title":"Proteomics"},{"issue":"11","key":"3752_CR9","doi-asserted-by":"publisher","first-page":"e0188059","DOI":"10.1371\/journal.pone.0188059","volume":"12","author":"K Handy","year":"2017","unstructured":"Handy K, Rosen J, Gillan A, Smith R. Fast, axis-agnostic, dynamically summarized storage and retrieval for mass spectrometry data. PLoS ONE. 2017;12(11):e0188059.","journal-title":"PLoS ONE"},{"issue":"1","key":"3752_CR10","first-page":"392","volume":"18","author":"J Henning","year":"2018","unstructured":"Henning J, Tostengard A, Smith R. A peptide-level fully annotated dataset for quantitative evaluation of precursor-aware mass spectrometry data processing algorithms. J Proteome Res. 2018;18(1):392\u20138.","journal-title":"J Proteome Res"},{"issue":"11","key":"3752_CR11","doi-asserted-by":"publisher","first-page":"3774","DOI":"10.1021\/acs.jproteome.8b00451","volume":"17","author":"M Gutierrez","year":"2018","unstructured":"Gutierrez M, Handy K, Smith R. Quantitative evaluation of algorithms for isotopic envelope extraction via extracted ion chromatogram clustering. J Proteome Res. 2018;17(11):3774\u20139.","journal-title":"J Proteome Res"},{"key":"3752_CR12","doi-asserted-by":"crossref","unstructured":"Danchilla B. Three.js framework. In: Beginning WebGL for HTML5. 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