Damien Chaussabel

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 compares the transcriptomic profiles of LPS-induced immune responses in homeRNA and venous blood samples, showing homeRNA captures comparable inflammatory responses.

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

This study examines how rituximab and immune-checkpoint inhibitors affect immune responses to a COVID-19 booster vaccine, finding rituximab impairs interferon response and ICI maintains normal immune profiles.

This study evaluates RNA degradation in homeRNA-stabilized blood under varying shipping times and temperatures, finding that samples remain suitable for RNA sequencing under typical shipping conditions.

This study profiles the transcriptional responses to three mRNA vaccine doses, showing sustained polyfunctional immunity after a nine-month interval.

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 uses large language models to analyze spatial transcriptomics data from a murine melanoma model, identifying immunosuppressive mechanisms in the tumor microenvironment.

This study shows that IL-3 enhances anti-tumor immunity by promoting CTL-basophil interactions, improving CTL activity and tumor suppression.

The paper provides R scripts for analyzing and visualizing blood transcriptional module repertoires, demonstrating their application in septic patients' transcriptome data.

The paper examines gene expression changes across multiple organs during short-term fasting in mice, identifying a brain-liver-fats network with significant immune system regulation.

The paper investigates FAM129A expression in neutrophils exposed to sepsis serum using transcriptome data and confirms surface expression through bench validation.

The paper investigates NUDT16 transcript abundance in sepsis using omics data and public datasets, finding elevated levels in septic patients compared to controls.

The paper develops a systems-based approach to classify T-cell responses using transcriptome data from PBMCs stimulated with peptides, identifying new molecular patterns and transcription factors involved in antigen-specific responses.