<HashMap><database>biostudies-literature</database><scores/><additional><submitter>LeDuc RD</submitter><funding>HHS | NIH | National Institute of General Medical Sciences</funding><funding>NIDA NIH HHS</funding><funding>HHS | NIH | National Institute on Drug Abuse</funding><funding>Paul G. Allen Family Foundation</funding><funding>NIGMS NIH HHS</funding><pagination>796-805</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6442365</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>18(4)</volume><pubmed_abstract>Within the last several years, top-down proteomics has emerged as a high throughput technique for protein and proteoform identification. This technique has the potential to identify and characterize thousands of proteoforms within a single study, but the absence of accurate false discovery rate (FDR) estimation could hinder the adoption and consistency of top-down proteomics in the future. In automated identification and characterization of proteoforms, FDR calculation strongly depends on the context of the search. The context includes MS data quality, the database being interrogated, the search engine, and the parameters of the search. Particular to top-down proteomics-there are four molecular levels of study: proteoform spectral match (PrSM), protein, isoform, and proteoform. Here, a con</pubmed_abstract><journal>Molecular &amp; cellular proteomics : MCP</journal><pubmed_title>Accurate Estimation of Context-Dependent False Discovery Rates in Top-Down Proteomics.</pubmed_title><pmcid>PMC6442365</pmcid><funding_grant_id>11715</funding_grant_id><funding_grant_id>P41GM108569</funding_grant_id><funding_grant_id>P30 DA018310</funding_grant_id><funding_grant_id>P41 GM108569</funding_grant_id><funding_grant_id>P30DA018310</funding_grant_id><pubmed_authors>Fellers RT</pubmed_authors><pubmed_authors>Early BP</pubmed_authors><pubmed_authors>Greer JB</pubmed_authors><pubmed_authors>Thomas PM</pubmed_authors><pubmed_authors>Kelleher NL</pubmed_authors><pubmed_authors>Shams DP</pubmed_authors><pubmed_authors>LeDuc RD</pubmed_authors></additional><is_claimable>false</is_claimable><name>Accurate Estimation of Context-Dependent False Discovery Rates in Top-Down Proteomics.</name><description>Within the last several years, top-down proteomics has emerged as a high throughput technique for protein and proteoform identification. This technique has the potential to identify and characterize thousands of proteoforms within a single study, but the absence of accurate false discovery rate (FDR) estimation could hinder the adoption and consistency of top-down proteomics in the future. In automated identification and characterization of proteoforms, FDR calculation strongly depends on the context of the search. The context includes MS data quality, the database being interrogated, the search engine, and the parameters of the search. Particular to top-down proteomics-there are four molecular levels of study: proteoform spectral match (PrSM), protein, isoform, and proteoform. Here, a con</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Apr</publication><modification>2026-04-30T10:29:50.07Z</modification><creation>2025-04-04T09:44:41.883Z</creation></dates><accession>S-EPMC6442365</accession><cross_references><pubmed>30647073</pubmed><doi>10.1074/mcp.ra118.000993</doi><doi>10.1074/mcp.RA118.000993</doi></cross_references></HashMap>