Scientists leverage machine learning to decode gene regulation in the developing human brain

Massively parallel characterization and prediction of gene regulatory activity in the developing brain. Credit: Science (2024). DOI: 10.1126/science.adh0559 In a scientific feat that broadens our knowledge of genetic changes that shape brain development or lead to psychiatric disorders, a team of researchers combined high-throughput experiments and machine learning to analyze more than 100,000 sequences in human brain cells—and identify over 150 variants that likely cause disease. The study, from scientists at Gladstone Institutes and University of California, San Francisco (UCSF), establishes a comprehensive catalog of genetic sequences involved in brain Read More