https://t.co/TeDmYadwza
UCSF researchers call for precision-medicine approach that could identify targets for novel treatments.
“This study calls for a precision framework for future drug development,” said the study’s senior author, @jingjingSF PhD and a member of @IHG_at_UCSF
Preterm birth affects 1 in 10 infants, with few treatment options. But a UCSF-led study shows how precision medicine in pregnancy could change that. “This study calls for a precision framework for future drug development,” senior author Jingjing Li says. https://t.co/rW0ZP4PAwu
New work from @jingjingSF@wang156658 + team reveals who can benefit from preterm birth therapy, calling for a precision-medicine approach that could identify targets for novel treatments. To conduct the study, researchers developed a machine-learning framework. More via @UCSF
Integrative #MachineLearning analysis reveals genes associated with preterm labor + identifies potential drug targets. The work not only contributes to addressing preterm labor but also establishes a valuable method for studying other complex diseases. Congrats @jingjingSF + team
An integrative #MachineLearning analysis reveals the genetic architecture in preterm labor, unveils its druggable genome, and provides a generalizable analytical framework for studying complex human diseases. https://t.co/4bUykcvLes