突变签名:从方法到机制。

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yoo-Ah Kim, Mark D M Leiserson, Priya Moorjani, Roded Sharan, Damian Wojtowicz, Teresa M Przytycka
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引用次数: 17

摘要

突变是进化的驱动力,但它们是许多疾病,尤其是癌症的基础。它们被认为是由DNA加工中的随机错误、自然发生的DNA损伤(例如,甲基化CpG位点的自发脱氨)、复制错误和DNA修复机制失调的组合引起的。高通量测序使得产生大型数据集来研究健康和疾病的突变过程成为可能。自2012年首次出现突变过程研究以来,该领域受到越来越多的关注,并且已经积累了大量的计算方法和生物医学应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mutational Signatures: From Methods to Mechanisms.

Mutations are the driving force of evolution, yet they underlie many diseases, in particular, cancer. They are thought to arise from a combination of stochastic errors in DNA processing, naturally occurring DNA damage (e.g., the spontaneous deamination of methylated CpG sites), replication errors, and dysregulation of DNA repair mechanisms. High-throughput sequencing has made it possible to generate large datasets to study mutational processes in health and disease. Since the emergence of the first mutational process studies in 2012, this field is gaining increasing attention and has already accumulated a host of computational approaches and biomedical applications.

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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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