计算机和临床中罕见癌症突变的中性演化。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-10-02 DOI:10.1038/s41540-024-00436-3
Robert A Beckman
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引用次数: 0

摘要

本文描述了罕见癌症突变中性进化的独特模型,并将其与基于无限位点近似的模型(即特定突变在任何瞬间只出现在一个细胞中)进行了对比。根据预测,在临床细胞数达到一定数量时,遗传多样性会出现爆炸性增长,这也可以解释癌症在临床过程中逐渐出现的难治性。广泛使用的无限位点假设可能不适用于临床癌症。
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Neutral evolution of rare cancer mutations in the computer and the clinic.

A distinct model of neutral evolution of rare cancer mutations is described and contrasted with models relying on the infinite sites approximation (that a specific mutation arises in only one cell at any instant). An explosion of genetic diversity is predicted at clinical cell numbers and may explain the progressive refractoriness of cancers during a clinical course. The widely used infinite sites assumption may not be applicable for clinical cancers.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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