BioinformaticsInternational Journal of Life Science and Pharma ResearchPeer-reviewed
Prediction of best features in heterogeneous Lung adenocarcinoma samples using Least Absolute Shrinking and Selection Operator.
Ateeq Muhammed Khaliq, R G SHARATHCHANDRA, Meenakshi Rajamohan
This study uses LASSO to predict key features in LUAD subtypes based on RNA-Seq data from TCGA, showing improved survival prediction through unsupervised clustering and feature selection.
DOI 10.22376/ijpbs/lpr.2019.9.4.l59-67