
Machine learning decodes microexon splicing to uncover rare autism-linked variants
A new study identifies hundreds of previously unknown neuronal microexons and uses machine learning to define the regulatory code governing their splicing. This approach reveals rare genetic variants that disrupt microexon regulation, linking them to autism spectrum disorder in individuals without known genetic causes.








