Welcome to NADCdb

NADCdb includes three core models namely "dNADC", "rNADC" and "iPredict" respectively. "rNADC" and its derivative tool are a risk assessment model with an impressive accuracy of 85.7% that is based on the expression patterns of key factors within the realms of immune suppression, chronic inflammation and oncogenic pathways, along with their regulated biological pathways. "dNADC", a diagnostic model with an accuracy of more than 80% in 13 out of 16 cancer types, is constructed by employing RF, CIT, and gene features that are defined as dysregulated expressed genes (DEGs) in both PLWH and cancer patients, alongside the upstream regulatory factors within the HIV DEGs. "iPredict" is designed to highlight the primary impact of HIV on the immune system and characterized 1,905 potential immune biomarkers that showed the same abnormal trends in both PLWH and cancer patients by categorizing PLWH and cancer patients into three groups based on different immune statuses. Importantly, a series of annotations and related analyses on these key factors are exhibited in NADCdb, including exhaustive functional annotations, phenotypic correlation analyses, PPI network mappings and cMAP analyses, that will contribute to delve understanding of their potential functions in NADC development. Additionally, NADCdb provided multiple user-friendly webpages including "Cancer" and "Gene" for queries of interest and instructions. In summary, NADCdb aims to provide new insights and impetus for the mechanisms, diagnosis and treatment of NADC.