Unveiling Immune Response Mechanisms in Mpox Infection Through Machine Learning Analysis of Time Series Gene Expression Data.

ABSTRACT: Monkeypox virus (Mpox) has recently drawn global attention due to outbreaks beyond its traditional endemic regions. Understanding the immune response to Mpox infection is essential for improving disease management and guiding vaccine development. In this study, we used several machine learning algorithms to analyze time series gene expression data from macaques infected with Mpox, aiming to uncover key immune-related genes involved in different stages of infection. The dataset covered early infection, late infection, and rechallenge phases. We applied nine feature ranking methods to analyze the feature importance, obtaining nine feature lists. Then, the incremental feature selection method was applied to each list to extract key genes and build efficient prediction models and classificatio

SUBMITTER: Ma Q 

PROVIDER: S-EPMC12301010 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature