Home
Our laboratory has two areas of interest – eicosanoid biology and molecular clocks.
In the case of eicosanoids, we are interested in the role they play in modulating the immune response in atherosclerosis and cancer, the promotion and restraint of cardiopulmonary fibrosis, in the response to viral infection and in stem cell biology. We are interested in the many factors that contribute to variability in the response to NSAIDs, including the microbiome, genomics, time of drug administration and metabolomics; the use of dynamic and network-based modelling to study drug response and the use of AI and machine learning approaches to develop paradigms predictive of efficacy and risk.
In the case of clocks, we are interested in how a decline in oscillatory function may contribute to age related phenotypes. We are integrating multiple remote sensing approaches with multi-omics analyses to characterize the human chronobiome and to identify time dependent networks that decline with age. Besides affording insight into the trajectory of aging this may afford the opportunity to obtain, in an unbiased fashion, mechanistic insights into time dependent disease phenotypes, such as non-dipping hypertension.
Publications
-
Segregate Assessment of Data Validity from the More Complex Issue of Fraud.
The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics. 2025 Mar 21;:1-3; Authors: FitzGerald GA -
Sleep disorders as risk factors for calcific aortic stenosis.
American journal of preventive cardiology. 2025 Jun;22:100958 Epub 2025 Mar 9; Authors: El Jamal N, Brooks TG, Skarke C, FitzGerald GA -
Generating Correlated Data for Omics Simulation.
bioRxiv : the preprint server for biology. 2025 Feb 6; Authors: Yang J, Grant GR, Brooks TG -
Sources of non-uniform coverage in short-read RNA-Seq data.
bioRxiv : the preprint server for biology. 2025 Feb 6; Authors: Brooks TG, Lahens NF, Mrčela A, Yang J, Purohit S, Naik A, Ricciotti E, Sengupta S, Choi PS, Grant GR -
MAJIQ-CLIN: A novel tool for the identification of Mendelian disease-causing variants from RNA-Seq data.
medRxiv : the preprint server for health sciences. 2025 Feb 2; Authors: Aicher JK, Issakova D, Slaff B, Jewell S, Lahens NF, Grant GR, Baralle D, Rosenfeld JA, Scott DA, Undiagnosed Diseases Network, Bhoj EJ, Barash Y