Computational Oncology & Cancer Genomics
We develop computational tools and algorithms to understand cancer biology and improve treatment outcomes.
Our Research
We specialize in developing algorithms for multi-modal analysis of cancer omics data, creating tools to discover insights into tumor evolution and treatment efficacy.
Connected Data
We lead initiatives in federated cancer data infrastructure, working with global consortiums to build frameworks that improve cancer research and care.
Open Science
We embrace open science principles, contributing to Bioconductor and sharing tools with the research community to accelerate cancer research globally.
Highlights
Recent Publications
Correspondence analysis for dimension reduction, batch integration, and visualization of single-cell RNA-seq data
Hsu LL, Culhane AC (2023) Scientific Reports
Anti-CAIX BBζ CAR4/8 T cells exhibit superior efficacy in a ccRCC mouse model
Wang Y, Buck A, Grimaud M, Culhane AC, et al. (2022) Molecular Therapy Oncolytics
Latest News
New Grant Award
Our lab has received funding for all-island eHealth research in cancer.
RTE Brainstorm Article
Prof Aedin Culhane and Prof Mark Lawler spoke with RTE Brainstorm about the pressing need for harmonization of clinical cancer health data.