Amit R. Majithia

The paper identifies ancestry-specific T2D risk variants in South Asian populations through exome-wide association study and functional validation.

This paper introduces a method using isotope tracing and mass isotopomer distributions to identify novel metabolites in mass spectrometry data, achieving 62% identification of unknown peaks.

This paper introduces a Transformer model called G2PT to predict metabolic traits from genetic variants and shows it outperforms existing methods across populations.

The paper identifies missing variants in the UK Biobank exome data due to incorrect read alignment and shows they can be recovered by adjusting alignment parameters.

The paper develops a paralog conservation score to identify disease-associated genes and shows that disease variants are enriched at conserved sites across gene families.