Publisher Correction: Machine learning prediction of prime editing efficiency across diverse chromatin contexts.

IF 33.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Nature biotechnology Pub Date : 2024-08-12 DOI:10.1038/s41587-024-02383-0

Nicolas Mathis, Ahmed Allam, András Tálas, Lucas Kissling, Elena Benvenuto, Lukas Schmidheini, Ruben Schep, Tanav Damodharan, Zsolt Balázs, Sharan Janjuha, Eleonora I Ioannidi, Desirée Böck, Bas van Steensel, Michael Krauthammer, Gerald Schwank

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出版商更正：机器学习预测不同染色质背景下的素材编辑效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature biotechnology 工程技术-生物工程与应用微生物

CiteScore

63.00

自引率

1.70%

发文量

382

审稿时长

3 months

期刊介绍： Nature Biotechnology is a monthly journal that focuses on the science and business of biotechnology. It covers a wide range of topics including technology/methodology advancements in the biological, biomedical, agricultural, and environmental sciences. The journal also explores the commercial, political, ethical, legal, and societal aspects of this research. The journal serves researchers by providing peer-reviewed research papers in the field of biotechnology. It also serves the business community by delivering news about research developments. This approach ensures that both the scientific and business communities are well-informed and able to stay up-to-date on the latest advancements and opportunities in the field. Some key areas of interest in which the journal actively seeks research papers include molecular engineering of nucleic acids and proteins, molecular therapy, large-scale biology, computational biology, regenerative medicine, imaging technology, analytical biotechnology, applied immunology, food and agricultural biotechnology, and environmental biotechnology. In summary, Nature Biotechnology is a comprehensive journal that covers both the scientific and business aspects of biotechnology. It strives to provide researchers with valuable research papers and news while also delivering important scientific advancements to the business community.