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Recently, many studies have begun to use machine learning technology to analyze the enormous data generated by nanopores. Unfortunately, the success of this technology is due to the extensive labeled data, which often suffer from enormous labor costs. Therefore, there is an urgent need for a novel technology that can not only rapidly analyze nanopore data with high-throughput, but also significantly reduce the cost of labeling. To achieve the above goals, we introduce active learning to alleviate the enormous labor costs by selecting the samples that need to be labeled. This work applies several advanced active learning technologies to the nanopore data, including the RNA classification dataset (RNA-CD) and the Oxford Nanopore Technologies barcode dataset (ONT-BD). Due to the complexity of the nanopore data (with noise sequence), the bias constraint is introduced to improve the sample selection strategy in active learning. Results: The experimental results show that for the same performance metric, 50% labeling amount can achieve the best baseline performance for ONT-BD, while only 15% labeling amount can achieve the best baseline performance for RNA-CD. Crucially, the experiments show that active learning technology can assist experts in labeling samples, and significantly reduce the labeling cost. Active learning can greatly reduce the dilemma of difficult labeling of high-capacity nanopore data. We hope active learning can be applied to other problems in nanopore sequence analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The main program is available at https:\/\/github.com\/guanxiaoyu11\/AL-for-nanopore.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac764","type":"journal-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T13:30:52Z","timestamp":1669728652000},"source":"Crossref","is-referenced-by-count":13,"title":["Active learning for efficient analysis of high-throughput nanopore data"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3985-3900","authenticated-orcid":false,"given":"Xiaoyu","family":"Guan","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence , Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongnian","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence , Nanjing 211106, China"},{"name":"School of Computer Science, China University of Mining Technology , Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueying","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence , Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Shao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence , Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daoqiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence , Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,11,29]]},"reference":[{"key":"2023010805382538100_btac764-B1","doi-asserted-by":"crossref","first-page":"2086","DOI":"10.1529\/biophysj.104.042960","article-title":"Microscopic kinetics of DNA translocation through synthetic nanopores","volume":"87","author":"Aksimentiev","year":"2004","journal-title":"Biophys. 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