Category Archives: DBDS

Understanding the genetic factors that underlie the normal variation in cardiac anatomy is of great interest. In this study, Rodrigo Bonazzola et al. applied unsupervised geometric deep learning to phenotype the left ventricle using an MRI-derived three-dimensional mesh representation (as depicted on the cover). We show that this approach boosts genetic discovery and provides deeper insights into the genetic underpinnings of cardiac morphology. Check out https://lnkd.in/edrvTg2W

Tanveer Syeda-Mahmood’s research featured in cover story for Nature Medicine Intelligence

Understanding the genetic factors that underlie the normal variation in cardiac anatomy is of great interest. In this study, Rodrigo Bonazzola et al. applied unsupervised geometric deep learning to phenotype the left ventricle using an MRI-derived three-dimensional mesh representation (as depicted on the cover). We show that this approach boosts genetic discovery and provides deeper insights into the genetic underpinnings of cardiac morphology.

Check out https://lnkd.in/edrvTg2W

The ClinGen Pharmacogenomics Working Group: Developing frameworks for evaluating pharmacogenomic gene validity and actionability Read it here: https://www.sciencedirect.com/science/article/pii/S294977442400222X Generating a framework for curating mechanism of disease in monogenic conditions: A consensus effort of the Gene Curation Coalition* Read it here: https://www.gimopen.org/article/S2949-7744(24)00622-8/fulltext

The ClinGen Pharmacogenomics Working Group: Exploring new directions and the evolution of PGx and genomic medicine

The ClinGen Pharmacogenomics Working Group: Developing frameworks for evaluating pharmacogenomic gene validity and actionability
Read it here: https://www.sciencedirect.com/science/article/pii/S294977442400222X

Generating a framework for curating mechanism of disease in monogenic conditions: A consensus effort of the Gene Curation Coalition*
Read it here: https://www.gimopen.org/article/S2949-7744(24)00622-8/fulltext