深度学习改进了对 CRISPR-Cpf1 引导 RNA 活性的预测

IF 33.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Nature biotechnology Pub Date : 2018-01-29 DOI:10.1038/nbt.4061

Hui Kwon Kim, Seonwoo Min, Myungjae Song, Soobin Jung, Jae Woo Choi, Younggwang Kim, Sangeun Lee, Sungroh Yoon, Hyongbum (Henry) Kim

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引用次数: 219

摘要

利用深度学习结合靶序列和染色质可及性数据提高 CRISPR-Cpf1 引导 RNA 活性的准确性我们提出了两种预测 AsCpf1 引导 RNA 活性的算法。我们在一个基于卷积神经网络的深度学习框架中使用了 15,000 个目标序列的 Indel 频率来训练 Seq-deepCpf1。然后，我们结合染色质可及性信息，为可获得此类信息的细胞系创建了性能更好的 DeepCpf1 算法，结果表明这两种算法在我们自己的数据集和已发表的数据集上都优于以前的机器学习算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity

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Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity

Using deep learning to combine target sequence and chromatin accessibility data boosts the accuracy of CRISPR–Cpf1 guide RNA activity We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

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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.