Alexander M. Lesokhin

Fate-AI improves cancer detection sensitivity and generalization by integrating fragmentomic and methylation features from cfDNA sequencing.

This study analyzes whole-genome sequencing data from multiple myeloma patients to show that the timing of genetic events, not just their presence, affects clinical outcomes.

The paper introduces FLORAL, a method for analyzing longitudinal microbiome data to identify biomarkers associated with time-varying outcomes, showing improved sensitivity and FDR control in simulations and real-world applications.

This study shows copy number signatures predict chromothripsis in multiple myeloma and link to poor clinical outcomes using whole genome and exome sequencing data.