Anil Kumar Giri

The paper develops a machine learning model to identify patient-specific multi-targeting therapies using single-cell transcriptomic data for hematological cancers and solid tumors.

ScType automates cell-type identification from scRNA-seq data using marker genes, achieving accurate and unbiased annotations across human and mouse tissues.

The paper identifies DNA methylation signatures and risk modules associated with T2DM using EWAS and network analysis, revealing JUP as a regulator of a co-methylated risk module.

This paper develops a computational-experimental approach to design patient-specific drug combinations for AML that are synergistic and minimally toxic.

This study identifies novel genetic loci associated with BMI in Indians through GWAS and explores their epigenetic and regulatory mechanisms.

SynToxProfiler prioritizes drug combinations by integrating synergy, efficacy, and toxicity profiles to improve clinical success likelihood.