Niksa Blonder, Benjamin C Orsburn, Josip Blonder, Carlos A Gonzalez
{"title":"Visual mass-spec share (vMS-Share): a new public web-based mass spectrometry visualization and data mining repository.","authors":"Niksa Blonder, Benjamin C Orsburn, Josip Blonder, Carlos A Gonzalez","doi":"10.4172/0974-276X.1000495","DOIUrl":null,"url":null,"abstract":"<p><p>Herein we introduce the Visual Mass-Spec Share (vMS-Share), a new public mass spectrometric (MS) repository and data mining website/resource freely accessible at https://vmsshare.nist.gov. vMS-Share is a web-based application developed for instant visualization of raw MS data with integrated display of metadata optimized for the sharing of proteomics and metabolomics experimental results. Each MS-based identification is linked to a given experiment and the entire experimental data can then be viewed using the link associated with a given peptide and/or small molecule. Interactive and user-friendly visualizations are provided to the user via variety of easily accessible search filters.</p>","PeriodicalId":73911,"journal":{"name":"Journal of proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6605085/pdf/nihms-1530821.pdf","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/0974-276X.1000495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Herein we introduce the Visual Mass-Spec Share (vMS-Share), a new public mass spectrometric (MS) repository and data mining website/resource freely accessible at https://vmsshare.nist.gov. vMS-Share is a web-based application developed for instant visualization of raw MS data with integrated display of metadata optimized for the sharing of proteomics and metabolomics experimental results. Each MS-based identification is linked to a given experiment and the entire experimental data can then be viewed using the link associated with a given peptide and/or small molecule. Interactive and user-friendly visualizations are provided to the user via variety of easily accessible search filters.