Philipp Sergeev

This study uses scRNA-seq to analyze AML patient samples across disease stages, identifying immune dysregulation and potential therapeutic targets.

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.

This study identifies molecular mechanisms of carfilzomib resistance in multiple myeloma using multi-omics data from cell lines and patient samples, revealing potential drug combinations to overcome resistance.

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