ナノポアシーケンシング技術、バイオインフォマティクスと応用

Nanopore sequencing technology, bioinformatics and applications | Nature Biotechnology Skip to main content Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Subjects Bioinformatics Genome informatics Sequencing Abstract Rapid advances in nanopore technologies for sequencing single long DNA and RNA molecules have led to substantial improvements in accuracy, read length and throughput. These breakthroughs have required extensive development of experimental and bioinformatics methods to fully exploit nanopore long reads for investigations of genomes, transcriptomes, epigenomes and epitranscriptomes. Nanopore sequencing is being applied in genome assembly, full-length transcript detection and base modification detection and in more specialized areas, such as rapid clinical diagnoses and outbreak surveillance. Many opportunities remain for improving data quality and analytical approaches through the development of new nanopores, base-calling methods and experimental protocols tailored to particular applications. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution Access options Access through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription 9,800 Yen / 30 days cancel any time Learn more Subscription info for Japanese customers We have a dedicated website for our Japanese customers. Please go to natureasia.com to subscribe to this journal. Go to natureasia.com Buy this article Purchase on SpringerLink Instant access to the full article PDF. ￥ 4,980 Prices may be subject to local taxes which are calculated during checkout Fig. 1: Principle of nanopore sequencing. The alternative text for this image may have been generated using AI. Fig. 2: ONT sequencing data improvement over time. The alternative text for this image may have been generated using AI. Fig. 3: Library preparation workflow for ONT sequencing. The alternative text for this image may have been generated using AI. Fig. 4: Analyses of ONT sequencing data. The alternative text for this image may have been generated using AI. Fig. 5: Applications of ONT sequencing. The alternative text for this image may have been generated using AI. 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