The research teams of Dr. Chien-Ling Lin at the Institute of Molecular Biology, and Dr. Yen-Tsung Huang at the Institute of Statistical Science, Academia Sinica, use massively parallel splicing assay to diagnose and model splicing errors of human intronic mutations. The learned model is highly accurate and facilitates the identification of health-related splicing errors in populations. This study offers the functional interpretation of intronic mutations for the precision health, and was published in Nature Structural & Molecular Biology.

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Mechanism and Prediction of Splicing Errors from Human Intronic Mutations