Dmitry Rychkov

The paper introduces the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets for comparative vaccine response analysis.

The paper identifies a pre-vaccination transcriptional state linked to pro-inflammatory genes that predicts higher antibody responses to multiple vaccines.

This paper identifies 13 biomarkers for rheumatoid arthritis using cross-tissue transcriptomic data and machine learning, validated across multiple datasets and showing clinical utility.

This study uses single-cell RNA sequencing to analyze Tocilizumab-treated PBMCs, showing reduced inflammatory gene expression in monocytes, supporting its potential to mitigate cytokine storms in COVID-19.

The paper develops a molecular and cellular instability score to reclassify histologically stable kidney allografts, identifying those with molecular signatures of acute rejection and predicting clinical outcomes.