Investigation of the performance of driver mutation identification methods using biological networks and enriched biological networks

  • Alfredo Guilherme da Silva Souza USP
  • Adenilso Simao USP


Several computational methods allow identifying genes related to cancer (driver mutation) through patient mutation data and biological networks. Usually, networks are not built focusing on biological activities associated with cancer because they are designed for general use. In this study, we investigate the performance of methods for identifying driver mutations using biological networks and enriched biological networks, applying a gene prioritization method to classify genes associated with cancer understudy in the biological network. The results indicated that employing the enrichment method helped identify different driver genes in all cases.


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SOUZA, Alfredo Guilherme da Silva; SIMAO, Adenilso. Investigation of the performance of driver mutation identification methods using biological networks and enriched biological networks. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 22. , 2022, Teresina. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 84-95. ISSN 2763-8952. DOI:

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