Karolina Palucka

The paper introduces SparTile, a computational method for analyzing multiplex proteomics images to identify clinically relevant spatial microenvironments in TNBC, finding specific markers and distances associated with poor survival.

The paper validates an LLM-guided gene prioritization framework for sepsis and tests its generalizability to obesity and infection using clinical and proteomic data.

This study shows that bacterial species and individual donors differentially modulate airway gene expression and alternative splicing in human epithelial cells.

This paper develops a framework using large language models for gene prioritization, validated against literature, identifying 30 high-confidence therapeutic candidates for sepsis.

The paper identifies intron retention in STAT2 as a regulator of immune signaling and a predictor of immunotherapy response in lung cancer.

This paper introduces a method using Large Language Models to perform deep functional profiling of gene sets, demonstrating its ability to uncover detailed immune functions and improve upon traditional annotation tools.

This paper develops an API-driven workflow using GPT-4 to automate candidate gene prioritization, demonstrating high consistency and scalability in identifying sepsis-related genes.

This study creates a single-cell aging atlas of mouse mammary tissues, identifying shared epigenomic and transcriptomic changes between aging and cancer.

The paper uses long-read RNA sequencing to identify novel isoforms in breast cancer, finding splicing events associated with patient survival.