Network-Based Logistic Classification with an Enhanced L1/2 Solver Reveals Biomarker and Subnetwork Signatures for Diagnosing Lung Cancer - Liang Yong

Identifying biomarker and signaling pathway is a critical step in genomic studies, in which the regularization method is a widely used feature extraction approach. However, most of the regularizers are based on [subscript] L1 [/subscript]-norm and their results are not good enough for sparsity and interpretation and are asymptotically biased, especially in genomic research. Recently, we gained a large amount of molecular interaction information about the disease-related biological processes and gathered them through various databases, which focused on many aspects of biological systems. In this paper, we use an enhanced [subscript] L1/2 [/subscript] penalized solver to penalize network-constrained logistic regression model called an enhanced [subscript] L1/2 [/subscript] net, where the predictors are based on gene-expression data with biologic network knowledge. Extensive simulation studies showed that our …