For example, researchers can use the model to predict what will happen to a protein when there’s a mistake in part of the regulatory code. Mutations in splicing instructions have already been linked to diseases such as spinal muscular atrophy, a leading cause of infant death, and some forms of colorectal cancer. In the new study, researchers used the trained model to analyze genetic data from people afflicted with some of those diseases. The scientists identified some known mutations linked to these maladies, verifying that the model works. They picked out some new candidate mutations as well, most notably for autism.
One of the benefits of the model, Frey said, is that it wasn’t trained using disease data, so it should work on any disease or trait of interest. The researchers plan to make the system publicly available, which means that scientists will be able to apply it to many more diseases.