{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mtim-rapid-and-accurate-transcript","title":"mTim: Rapid and accurate transcript reconstruction from RNA-Seq data","arxiv_id":"1309.5211","date":"2013-09-20","proceeding":null,"authors":["Georg Zeller","Nico Goernitz","Andre Kahles","Jonas Behr","Pramod Mudrakarta","Soeren Sonnenburg","Gunnar Raetsch"],"abstract":"Recent advances in high-throughput cDNA sequencing (RNA-Seq) technology have\nrevolutionized transcriptome studies. A major motivation for RNA-Seq is to map\nthe structure of expressed transcripts at nucleotide resolution. With accurate\ncomputational tools for transcript reconstruction, this technology may also\nbecome useful for genome (re-)annotation, which has mostly relied on de novo\ngene finding where gene structures are primarily inferred from the genome\nsequence. We developed a machine-learning method, called mTim (margin-based\ntranscript inference method) for transcript reconstruction from RNA-Seq read\nalignments that is based on discriminatively trained hidden Markov support\nvector machines. In addition to features derived from read alignments, it\nutilizes characteristic genomic sequences, e.g. around splice sites, to improve\ntranscript predictions. mTim inferred transcripts that were highly accurate and\nrelatively robust to alignment errors in comparison to those from Cufflinks, a\nwidely used transcript assembly method.","url_abs":"http://arxiv.org/abs/1309.5211v1","url_pdf":"http://arxiv.org/pdf/1309.5211v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mtim-rapid-and-accurate-transcript","repo_url":"https://github.com/nicococo/mTIM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}