Research in the Luna laboratory seeks to understand disease biology through the development of mechanistic and statistical computational models that involve various aspects of gene regulation, genomic alterations, proteomics and metabolism both through pan-cancer analysis and analysis of specific cancers, including rare cancers. The goal of the work is to address key questions in our understanding of network properties of human disease and to utilize this knowledge to improve treatment options and clinical decision-making through interpretable methodologies.

In support of FAIR (Findable, Accessible, Interoperable, and Reusable) principles of scientific research, Dr. Luna has been a long-term member of communities working on standardized representations of biological data (e.g., the Biological Pathway Exchange format and the Systems Biology Graphical Notation). These data representations are key components of several molecular interaction databases and a basis for the network-based methods and software tools that Dr. Luna has worked with colleagues to build in order to address key questions in our understanding of network properties of human disease.