Welcome to NADCdb

NADCdb includes three core models namely "dNADC", "rNADC" and "iPredict" respectively. "rNADC" and its derivative tool was the first to utilize genes, that within the realms of immune suppression, chronic inflammation and oncogenic pathways, with abnormal expression trends as candidates, employing bidirectional stepwise regression and logistic regression to assess the risk of PLWH developing 21 NADCs. "dNADC" integrated patients' dysregulated genes and their regulatory networks, using Random Forest (RF) and Conditional Inference Trees (CIT) to identify key drivers influencing NADC progression with an accuracy exceeding 75%. "iPredict" is designed to highlight the primary impact of HIV on the immune system and identified 1,905 key immunobiomarkers for 16 NADCs based on distinct three immune statuses (CD4-, CD8+, CD4-CD8+) of patients. Importantly, the multi-dimensional analysis of the key factors was performed, including depth functional annotations, phenotype correlations, protein-protein interaction (PPI) networks, TF-miRNA-target regulatory networks and CMap drug prediction, to deeply dissect their pathogenic mechanisms in regulating NADCs. 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.