{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T09:31:30Z","timestamp":1786181490323,"version":"3.56.0"},"reference-count":9,"publisher":"Oxford University Press (OUP)","issue":"5","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["HG000783"],"award-info":[{"award-number":["HG000783"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"German Research Foundation","doi-asserted-by":"crossref","award":["STA 1009\/10-1"],"award-info":[{"award-number":["STA 1009\/10-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.<\/jats:p>\n               <jats:p>Results: We present BRAKER1, a pipeline for unsupervised RNA-Seq-based genome annotation that combines the advantages of GeneMark-ET and AUGUSTUS. As input, BRAKER1 requires a genome assembly file and a file in bam-format with spliced alignments of RNA-Seq reads to the genome. First, GeneMark-ET performs iterative training and generates initial gene structures. Second, AUGUSTUS uses predicted genes for training and then integrates RNA-Seq read information into final gene predictions. In our experiments, we observed that BRAKER1 was more accurate than MAKER2 when it is using RNA-Seq as sole source for training and prediction. BRAKER1 does not require pre-trained parameters or a separate expert-prepared training step.<\/jats:p>\n               <jats:p>Availability and implementation: BRAKER1 is available for download at http:\/\/bioinf.uni-greifswald.de\/bioinf\/braker\/ and http:\/\/exon.gatech.edu\/GeneMark\/.<\/jats:p>\n               <jats:p>Contact: \u00a0katharina.hoff@uni-greifswald.de or borodovsky@gatech.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv661","type":"journal-article","created":{"date-parts":[[2015,11,12]],"date-time":"2015-11-12T02:10:31Z","timestamp":1447294231000},"page":"767-769","source":"Crossref","is-referenced-by-count":1158,"title":["BRAKER1: Unsupervised RNA-Seq-Based Genome Annotation with GeneMark-ET and AUGUSTUS"],"prefix":"10.1093","volume":"32","author":[{"given":"Katharina J.","family":"Hoff","sequence":"first","affiliation":[{"name":"1 Ernst Moritz Arndt Universit\u00e4t Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Lange","sequence":"additional","affiliation":[{"name":"1 Ernst Moritz Arndt Universit\u00e4t Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre","family":"Lomsadze","sequence":"additional","affiliation":[{"name":"3 Joint Georgia Tech and Emory University Wallace H Coulter Department of Biomedical Engineering, Atlanta, GA 30332, USA and"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Borodovsky","sequence":"additional","affiliation":[{"name":"2 School of Computational Science and Engineering, Atlanta, GA 30332, USA,"},{"name":"3 Joint Georgia Tech and Emory University Wallace H Coulter Department of Biomedical Engineering, Atlanta, GA 30332, USA and"},{"name":"4 Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Stanke","sequence":"additional","affiliation":[{"name":"1 Ernst Moritz Arndt Universit\u00e4t Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2015,11,11]]},"reference":[{"key":"2023020110451319000_btv661-B1","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.cois.2015.02.008","article-title":"Current methods for automated annotation of protein-coding genes","volume":"7","author":"Hoff","year":"2015","journal-title":"Curr. Opin. Insect Sci."},{"key":"2023020110451319000_btv661-B2","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1186\/1471-2105-12-491","article-title":"MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects","volume":"12","author":"Holt","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023020110451319000_btv661-B3","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1186\/1471-2105-4-50","article-title":"Eval: a software package for analysis of genome annotations","volume":"4","author":"Keibler","year":"2003","journal-title":"BMC Bioinformatics"},{"key":"2023020110451319000_btv661-B4","doi-asserted-by":"crossref","first-page":"e119","DOI":"10.1093\/nar\/gku557","article-title":"Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm","volume":"42","author":"Lomsadze","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"2023020110451319000_btv661-B5","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1186\/1471-2105-15-229","article-title":"SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models","volume":"15","author":"Reid","year":"2014","journal-title":"BMC Bioinformatics"},{"key":"2023020110451319000_btv661-B6","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1093\/bioinformatics\/btn013","article-title":"Using native and syntenically mapped cDNA alignments to improve de novo gene finding","volume":"24","author":"Stanke","year":"2008","journal-title":"Bioinformatics"},{"key":"2023020110451319000_btv661-B7","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1038\/nmeth.2714","article-title":"Assessment of transcript reconstruction methods for RNA-seq","volume":"10","author":"Steijger","year":"2013","journal-title":"Nat. Methods"},{"key":"2023020110451319000_btv661-B8","doi-asserted-by":"crossref","first-page":"1979","DOI":"10.1101\/gr.081612.108","article-title":"Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training","volume":"18","author":"Ter-Hovhannisyan","year":"2008","journal-title":"Genome Res."},{"key":"2023020110451319000_btv661-B9","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1186\/s12864-015-1344-4","article-title":"CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts","volume":"16","author":"Testa","year":"2015","journal-title":"BMC Genomics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/5\/767\/49017707\/bioinformatics_32_5_767.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/5\/767\/49017707\/bioinformatics_32_5_767.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T22:01:40Z","timestamp":1675288900000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/5\/767\/1744611"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,11,11]]},"references-count":9,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2016,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btv661","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,3,1]]},"published":{"date-parts":[[2015,11,11]]}}}