EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer.

ABSTRACT:

Background

Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.

Methods

In this work, we study somatic mutation data consists of 450 metastatic breast tumor samples from cBio Cancer Genomics Portal. We use four software tools to extract features from this data. Then, an ensemble classifier (EC) learning algorithm called EARN (Ensemble of Artificial Neural Network, Random Forest, and non-linear Support Vector Machine) is proposed to evaluate plausible driver genes for metastatic breast cancer (MBCA). The decision-making strategy for the proposed ensemble machine is based on the aggregation of the predicted scores obtained from i

SUBMITTER: Mirsadeghi L 

PROVIDER: S-EPMC8105935 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature