A proposal of a graph-based computational method for ranking significant set of related genes in cancer

• Jorge Francisco Cutigi IFSP
• Adriane Feijó Evangelista USP
• Adenilso da Silva Simão CPOM

DOI: https://doi.org/10.5753/sbcas.2019.6266

Resumo

Identifying significant mutations in cancer is a key point in Cancer Genomics, and it is one of the biggest challenges in the area. Computational methods for identifying significant mutations have been developed in recent years. In this work, we present a proposal of a flexible computational method with an extensive biological base for ranking significant set of related genes in cancer. Our method considers data about mutations, type of mutations, gene interaction networks and mutual exclusivity pattern.

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