{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T14:00:34Z","timestamp":1774533634473,"version":"3.50.1"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"Supplement_1","license":[{"start":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T00:00:00Z","timestamp":1626048000000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 GM121818"],"award-info":[{"award-number":["R01 GM121818"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35 GM119536"],"award-info":[{"award-number":["R35 GM119536"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P41 GM103533"],"award-info":[{"award-number":["P41 GM103533"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000888","name":"Keck Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000888","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m\/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a \u2018spectral library\u2019), but this approach is expensive because the libraries do not typically generalize well across laboratories.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we propose DIAmeter, a search engine that detects peptides in DIA data using only a peptide sequence database. Although some existing library-free DIA analysis methods (i) support data generated using both wide and narrow isolation windows, (ii) detect peptides containing post-translational modifications, (iii) analyze data from a variety of instrument platforms and (iv) are capable of detecting peptides even in the absence of detectable signal in the survey (MS1) scan, DIAmeter is the only method that offers all four capabilities in a single tool.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The open source, Apache licensed source code is available as part of the Crux mass spectrometry analysis toolkit (http:\/\/crux.ms).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab284","type":"journal-article","created":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T11:38:25Z","timestamp":1619523505000},"page":"i434-i442","source":"Crossref","is-referenced-by-count":28,"title":["DIAmeter: matching peptides to data-independent acquisition mass spectrometry data"],"prefix":"10.1093","volume":"37","author":[{"given":"Yang Young","family":"Lu","sequence":"first","affiliation":[{"name":"Department of Genome Sciences, University of Washington , Seattle, WA 98195, USA"}]},{"given":"Jeff","family":"Bilmes","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Washington , Seattle, WA 98195, USA"},{"name":"Paul G. Allen School of Computer Science and Engineering, University of Washington , Seattle, WA 98195, USA"}]},{"given":"Ricard A","family":"Rodriguez-Mias","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington , Seattle, WA 98195, USA"}]},{"given":"Judit","family":"Vill\u00e9n","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington , Seattle, WA 98195, USA"}]},{"given":"William Stafford","family":"Noble","sequence":"additional","affiliation":[{"name":"Department of Genome Sciences, University of Washington , Seattle, WA 98195, USA"},{"name":"Paul G. Allen School of Computer Science and Engineering, University of Washington , Seattle, WA 98195, USA"}]}],"member":"286","published-online":{"date-parts":[[2021,7,12]]},"reference":[{"key":"2023071014352912100_btab284-B1","first-page":"327","author":"Bai","year":"2016"},{"key":"2023071014352912100_btab284-B2","article-title":"DeepLC can predict retention times for peptides that carry as-yet unseen modifications","author":"Bouwmeester","year":"2020","journal-title":"BioRxiv"},{"key":"2023071014352912100_btab284-B3","doi-asserted-by":"crossref","first-page":"2296","DOI":"10.1074\/mcp.RA117.000314","article-title":"Optimization of experimental parameters in data-independent mass spectrometry significantly increases depth and reproducibility of results","volume":"16","author":"Bruderer","year":"2017","journal-title":"Mol. Cell. 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