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.

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识别癌症驱动突变的方法：从计算角度看的教程

癌症是一种复杂的疾病，由个体一生中基因改变的积累引起。这种改变被称为基因突变，可以分为两组：（1）乘客突变，不导致癌症；（2）驱动突变，对癌症有重要意义，并导致癌症的发生和发展。癌细胞会发生大量突变，其中大多数是乘客，很少是司机。驱动突变的鉴定是癌症基因组学中的一个关键点，也是最大的挑战之一。在癌症生物信息学中已经开发了许多用于此目的的计算方法。这种计算方法很复杂，通常以高级抽象来描述。本教程从计算的角度详细介绍了一些经典的计算方法，