Network science approach for enrichment analysis in breast and ovarian cancer

Abstract

The imprecise identification of cancer characteristics can lead the patient to aggressive and unnecessary treatments. Therefore, it is crucial to identify tumor intrinsic characteristics more precisely to propose individual-tailored treatment. In this work, we present a brief explanation of fundamentals and researches in computer graph theory that seek to solve problems of identification, classification, and characterization of certain cancer types. We proposed a novel solution based on Network Science to find a list of genes for enrichment analysis in Breast and Ovarian cancer using proteogenomic information. In our results, we show that our approach is capable of capturing biological processes and sets of genes related to cancer and other processes, which opens a range of possibilities for further studies.