Molecular pathway identification using biological network-regularized logistic models

Abstract

Logistic regression with graph Laplacian regularization is an effective algorithm for identifying key pathways and modules associated with disease subtypes. With the rapid expansion of our knowledge of biological regulatory networks, this approach will become more accurate and increasingly useful for mining transcriptomic, epi-genomic, and other types of genome wide association studies.