Recently, there is an explosion of molecular data from genomic, proteomics, metabolomics and structural data. The genomic data are often massive and have complex relationships with clinical responses. Manual handling of genomic and epigenetic data is almost impossible. Artificial intelligence (AI) and deep learning play an important role in interpreting the huge and complex data. AI guides the researchers and clinicians to predict regulatory elements, variant effect, gene expression, splicing, assessing chromatin accessibility, epigenomics, and also to predict the presence, type, and risk of disease from DNA sequencing data. In the present chapter, the details of molecular data interpretation and the key technologies are discussed.