<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Pino L</submitter><funding>NIA NIH HHS</funding><funding>Belgian American Educational Foundation</funding><funding>Fonds Wetenschappelijk Onderzoek</funding><funding>National Institute on Aging</funding><pagination>3936-3943</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6824964</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>18(11)</volume><pubmed_abstract>For the 2018 YPIC Challenge, contestants were invited to try to decipher two unknown English questions encoded by a synthetic protein expressed in &lt;i>Escherichia coli&lt;/i>. In addition to deciphering the sentence, contestants were asked to determine the three-dimensional structure and detect any post-translation modifications left by the host organism. We present our experimental and computational strategy to characterize this sample by identifying the unknown protein sequence and detecting the presence of post-translational modifications. The sample was acquired with dynamic exclusion disabled to increase the signal-to-noise ratio of the measured molecules, after which spectral clustering was used to generate high-quality consensus spectra. De novo spectrum identification was used to deter</pubmed_abstract><journal>Journal of proteome research</journal><pubmed_title>2018 YPIC Challenge: A Case Study in Characterizing an Unknown Protein Sample.</pubmed_title><pmcid>PMC6824964</pmcid><funding_grant_id>F31 AG055257</funding_grant_id><pubmed_authors>Lin A</pubmed_authors><pubmed_authors>Pino L</pubmed_authors><pubmed_authors>Bittremieux W</pubmed_authors></additional><is_claimable>false</is_claimable><name>2018 YPIC Challenge: A Case Study in Characterizing an Unknown Protein Sample.</name><description>For the 2018 YPIC Challenge, contestants were invited to try to decipher two unknown English questions encoded by a synthetic protein expressed in &lt;i>Escherichia coli&lt;/i>. In addition to deciphering the sentence, contestants were asked to determine the three-dimensional structure and detect any post-translation modifications left by the host organism. We present our experimental and computational strategy to characterize this sample by identifying the unknown protein sequence and detecting the presence of post-translational modifications. The sample was acquired with dynamic exclusion disabled to increase the signal-to-noise ratio of the measured molecules, after which spectral clustering was used to generate high-quality consensus spectra. De novo spectrum identification was used to deter</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Nov</publication><modification>2026-04-16T11:10:23.706Z</modification><creation>2019-11-09T08:01:51Z</creation></dates><accession>S-EPMC6824964</accession><cross_references><pubmed>31556620</pubmed><doi>10.1021/acs.jproteome.9b00384</doi></cross_references></HashMap>