Ensemble outlier detection and gene selection in triple-negative breast cancer data.

Marta B LopesAndré VeríssimoEunice CarrasquinhaSandra CasimiroNiko BeerenwinkelSusana Vinga

Published in: BMC bioinformatics (2018)

The proposed ensemble outlier detection approach constitutes a robust procedure to identify abnormal cases and consensus covariates, which may improve biomarker selection for precision medicine applications. The method can also be easily extended to other regression models and datasets.

Keyphrases

loop mediated isothermal amplification
real time pcr
label free
convolutional neural network
genome wide
big data
neural network
gene expression
clinical practice
dna methylation
machine learning
sensitive detection
deep learning
data analysis
genome wide analysis