Developing neural network diagnostic models and potential drugs based on novel identified immune-related biomarkers for celiac disease.

ABSTRACT:

Background

As one of the most common intestinal inflammatory diseases, celiac disease (CD) is typically characterized by an autoimmune disorder resulting from ingesting gluten proteins. Although the incidence and prevalence of CD have increased over time, the diagnostic methods and treatment options are still limited. Therefore, it is urgent to investigate the potential biomarkers and targeted drugs for CD.

Methods

Gene expression data was downloaded from GEO datasets. Differential gene expression analysis was performed to identify the dysregulated immune-related genes. Multiple machine algorithms, including randomForest, SVM-RFE, and LASSO, were used to select the hub immune-related genes (HIGs). The immune-related genes score (IG score) and artificial neural network (ANN)

SUBMITTER: Shen T 

PROVIDER: S-EPMC10433645 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature