{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T14:25:45Z","timestamp":1747837545887},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation:\u2003The reliable identification of genes is a major challenge in genome research, as further analysis depends on the correctness of this initial step. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly available for gene finding. However, practical application in automated gene identification is still not the standard case. A particular challenge in including RNA-Seq data is the difficult handling of ambiguously mapped reads.<\/jats:p>\n               <jats:p>Results:\u2003We present GIIRA (Gene Identification Incorporating RNA-Seq data and Ambiguous reads), a novel prokaryotic and eukaryotic gene finder that is exclusively based on a RNA-Seq mapping and inherently includes ambiguously mapped reads. GIIRA extracts candidate regions supported by a sufficient number of mappings and reassigns ambiguous reads to their most likely origin using a maximum-flow approach. This avoids the exclusion of genes that are predominantly supported by ambiguous mappings. Evaluation on simulated and real data and comparison with existing methods incorporating RNA-Seq information highlight the accuracy of GIIRA in identifying the expressed genes.<\/jats:p>\n               <jats:p>Availability and implementation:\u2003GIIRA is implemented in Java and is available from https:\/\/sourceforge.net\/projects\/giira\/.<\/jats:p>\n               <jats:p>Contact:\u2003renardB@rki.de<\/jats:p>\n               <jats:p>Supplementary Information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt577","type":"journal-article","created":{"date-parts":[[2013,10,13]],"date-time":"2013-10-13T00:09:21Z","timestamp":1381622961000},"page":"606-613","source":"Crossref","is-referenced-by-count":10,"title":["GIIRA\u2014RNA-Seq driven gene finding incorporating ambiguous reads"],"prefix":"10.1093","volume":"30","author":[{"given":"Franziska","family":"Zickmann","sequence":"first","affiliation":[{"name":"Research Group Bioinformatics (NG4), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin S.","family":"Lindner","sequence":"additional","affiliation":[{"name":"Research Group Bioinformatics (NG4), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernhard Y.","family":"Renard","sequence":"additional","affiliation":[{"name":"Research Group Bioinformatics (NG4), Robert Koch-Institute, Nordufer 20, 13353 Berlin, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,10,11]]},"reference":[{"key":"2023012710430573400_btt577-B1","doi-asserted-by":"crossref","first-page":"3596","DOI":"10.1093\/bioinformatics\/bti609","article-title":"JIGSAW: integration of multiple sources of evidence for gene prediction","volume":"21","author":"Allen","year":"2005","journal-title":"Bioinformatics"},{"key":"2023012710430573400_btt577-B2","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1093\/nar\/29.12.2607","article-title":"GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. 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