Scientists at Southwestern University in California have used AI to identify thousands of genetic mutations in mammals.
The new study helped identify 101 new genes with a 95% chance, said Bruce Bitler, M.D. and director of the Center for Genetics (CGHD).
The authors of the new work have created software called Candidate Explorer (CE): it uses a machine-learning algorithm to identify chemically induced mutations that can cause damage to the immune system.
The new software determines the likelihood that a particular mutation is causing a malfunction in the mammalian body.
Bitler said the new AI will help researchers predict whether a mutation associated with a phenotype is dangerous. Candidate Explorer has already helped identify hundreds of genes with new functions in immunity. This will improve your understanding of how the immune system works and also help you find new ways to improve its functioning.
In order to understand the functions of certain mutations, the algorithm learns: it recreates a specific mutation in a new pedigree and tests the hypothesis about its functioning and causality. This is how the ptential functionality of the mutation can be assessed.