Professor Hua Yimin as a co-author published an article entitled“The human splicing code reveals new insights intothe genetic determinants of disease”in the top journal Science.They developed a machine learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of over 650,000 intronic and exonic variants reveals widespread patterns of mutation-driven aberrant splicing. Intronic disease mutations alter splicing nine times more often than common variants, and missense exonic disease mutations that least impact protein function are five times more likely to alter splicing than others. Tens of thousands of disease-causing mutations are detected, including those involved in cancers and spinal muscular atrophy.