Laura M. Amendola

The paper develops a standardized case-level categorization metric for genomic results across the CSER2 consortium to assess diagnostic yield and identify resolvable factors in inconclusive cases.

The paper develops a machine learning model to prioritize genes for newborn sequencing programs based on factors like evidence of disease natural history and treatment efficacy.

This paper develops a genome-wide cardiovascular disease genetic risk assessment test that includes monogenic conditions, risk alleles, pharmacogenomic variants, and polygenic risk scores, showing high performance and scalability.

The paper identifies de novo PRKAR1B variants in six individuals with neurodevelopmental disorder, autism, apraxia, and reduced pain sensitivity.

The paper identifies de novo variants in EIF2AK1 and EIF2AK2 associated with neurodevelopmental disorders and leukoencephalopathy, showing similar pathogenic mechanisms to CACH/VWM.