Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective

J Bioinform Comput Biol. 2020 Jun;18(3):2050016. doi: 10.1142/S021972002050016X.

Abstract

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.

Keywords: Cancer bioinformatics; computational methods; driver mutations.

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Gene Regulatory Networks
  • Genomics / methods*
  • Humans
  • Mutation*
  • Neoplasms / genetics*