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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective
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Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective

机译:癌症中司机突变识别的方法:从计算角度来看

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摘要

Cancer is a complex disease caused by the accumulation of genetic alterations during the individual's life. Such alterations are called genetic mutations and can be divided into two groups: (1) Passenger mutations, which are not responsible for cancer and (2) Driver mutations, which are significant for cancer and responsible for its initiation and progression. Cancer cells undergo a large number of mutations, of which most are passengers, and few are drivers. The identification of driver mutations is a key point and one of the biggest challenges in Cancer Genomics. Many computational methods for such a purpose have been developed in Cancer Bioinformatics. Such computational methods are complex and are usually described in a high level of abstraction. This tutorial details some classical computational methods, from a computational perspective, with the transcription in an algorithmic format towards an easy access by researchers.
机译:癌症是一种复杂的疾病,由个人生活中的遗传改变积累引起的疾病。 这种改变称为遗传突变,可分为两组:(1)对癌症和(2)次司机突变负责的乘客突变,这对癌症具有重要意义,并负责其启动和进展。 癌细胞经历大量突变,其中大多数是乘客,很少有司机。 驾驶员突变的识别是癌症基因组学中最大的挑战之一。 用于这种目的的许多计算方法已在癌症生物信息学中开发。 这种计算方法是复杂的并且通常以高级别的抽象描述。 本教程详细说明了一些经典计算方法,从计算透视,以算法格式转录到研究人员的轻松访问。

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