{"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/boassembler-a-bayesian-optimization-framework","title":"BOAssembler: a Bayesian Optimization Framework to Improve RNA-Seq Assembly Performance","arxiv_id":"1902.05235","date":"2019-02-14","proceeding":null,"authors":["Shunfu Mao","Yihan Jiang","Edwin Basil Mathew","Sreeram Kannan"],"abstract":"High throughput sequencing of RNA (RNA-Seq) can provide us with millions of\nshort fragments of RNA transcripts from a sample. How to better recover the\noriginal RNA transcripts from those fragments (RNA-Seq assembly) is still a\ndifficult task. For example, RNA-Seq assembly tools typically require\nhyper-parameter tuning to achieve good performance for particular datasets.\nThis kind of tuning is usually unintuitive and time-consuming. Consequently,\nusers often resort to default parameters, which do not guarantee consistent\ngood performance for various datasets.\n  Here we propose BOAssembler (https://github.com/olivomao/boassembler), a\nframework that enables end-to-end automatic tuning of RNA-Seq assemblers, based\non Bayesian Optimization principles. Experiments show this data-driven approach\nis effective to improve the overall assembly performance. The approach would be\nhelpful for downstream (e.g. gene, protein, cell) analysis, and more broadly,\nfor future bioinformatics benchmark studies.","url_abs":"http://arxiv.org/abs/1902.05235v1","url_pdf":"http://arxiv.org/pdf/1902.05235v1.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":"boassembler-a-bayesian-optimization-framework","repo_url":"https://github.com/olivomao/boassembler","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"bayesian-optimization","task_name":"Bayesian Optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}