肿瘤克隆进化分析:计算视角。

IF 0.9 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Paulo Henrique Ribeiro, Adenilso Simao
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引用次数: 0

摘要

癌症是一种复杂的疾病,它通过达尔文进化在细胞中发生基因突变,导致肿瘤内多个不同细胞群的发展,这一过程被称为克隆进化。虽然计算方法有助于利用基因测序数据分析癌症样本中的克隆进化,但准确识别肿瘤样本的克隆结构仍然是癌症基因组学中最大的挑战之一。近年来发展了几种用于分析癌症克隆进化的计算方法。然而,这些计算方法的算法是复杂的,并且经常在一个高层次的抽象描述。本文从计算的角度详细介绍了克隆进化分析的几种计算方法,有助于理解它们的作用机制。此外,一些方法已经在一个在线平台上实现,使研究人员能够轻松地运行和分析算法,并使这些方法适应他们的特定需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of clonal evolution in cancer: A computational perspective.

Cancer is a complex disease that progresses through Darwinian evolution in cells with genetic mutations, leading to the development of multiple distinct cell populations within tumors, a process known as clonal evolution. While computational methods aid in the analysis of clonal evolution in cancer samples using genetic sequencing data, accurately identifying the clonal structure of tumor samples remains one of the biggest challenges in Cancer Genomics. Several computational methods for analyzing clonal evolution in cancer have been developed in recent years. However, the algorithms of these computational methods are complex and often described at a high level of abstraction. This paper provides a detailed explanation of some computational methods for clonal evolution analysis from a computational perspective, aiding in understanding their mechanisms. Additionally, some methods have been implemented on an online platform, enabling researchers to easily run and analyze the algorithms, as well as adapt these methods to their specific needs.

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来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
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