Multi-Level Model to Predict Antibody Response to Influenza Vaccine Using Gene Expression Interaction Network Feature Selection.

ABSTRACT: Vaccination is an effective prevention of influenza infection. However, certain individuals develop a lower antibody response after vaccination, which may lead to susceptibility to subsequent infection. An important challenge in human health is to find baseline gene signatures to help identify individuals who are at higher risk for infection despite influenza vaccination. We developed a multi-level machine learning strategy to build a predictive model of vaccine response using pre-vaccination antibody titers and network interactions between pre-vaccination gene expression levels. The first-level baseline-antibody model explains a significant amount of variation in post-vaccination response, especially for subjects with large pre-existing antibody titers. In the second level, we clustered i

SUBMITTER: Parvandeh S 

PROVIDER: S-EPMC6462975 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature