Michael Elgart

CoSMIC improves microbial profiling by combining long-read and short-read sequencing with a novel integration framework, achieving higher resolution and accuracy in identifying microbial communities.

The paper introduces a parametric bootstrap method to compute confidence intervals for genetic correlations, applied to protein-protein networks from proteomics data.

The paper investigates how environmental factors disrupt epigenetic memory, leading to organ transformation in Drosophila through altered protein integrity and histone modifications.

This paper uses gradient boosted trees to improve polygenic risk prediction by capturing non-linear genetic effects and SNP interactions, showing significant increases in variance explained for multiple complex traits.

The paper estimates genetic and environmental correlations between complex phenotypes across different racial/ethnic groups and sexes using data from the TOPMed program.

This paper introduces SMURF, a method to combine 16S rRNA gene sequencing from multiple regions to improve microbial community resolution.