Satyarth Mishra Sharma

This study evaluates federated learning's effectiveness on genomic data using UK Biobank and 1000 Genomes Project datasets, showing performance close to centralized models despite data heterogeneity.

The paper uses a deep neural network with a Light Attention mechanism to predict protein stability changes from mutations, achieving high accuracy on a new mega dataset.

This paper compares nonlinear and linear models for genotype-to-phenotype prediction, showing nonlinear models can be more accurate with rich covariates and ensembling improves accuracy for asthma and hypothyroidism.

The paper presents methods to improve fetal variant calling accuracy in the presence of maternal cell contamination using Bayesian models and learned genotype-correction models.