The Systems Biology and Bioinformatics Core will support the Program Subprojects and Cores in data management and analysis. We will achieve this by providing statistical sen/ices, bioinformatics collaboration and data management across the entirety of the program project. Merging biostatistical expertise at the Mayo Clinic and bioinformatics expertise at the Buck Institute for Research on Aging Bioinformatics Core, together we represent a significant resource for participant investigators. We will achieve this goal through three service-based aims. First, we will provide bioinformatics collaboration through pathway analysis, network modeling and comparative genomic analysis of tissue specific effects in mice and humans. Second, we will provide data management sen/ices with the goal of integration and cross project analyses. Finally, we will provide biostatistical analysis to ensure that each experiment within the program project is sufficiently powered and the resulting analysis is quantitatively sound. Together this represents a comprehensive approach to providing quantitative methodologies to the project.

Public Health Relevance

Modern biomedical research is largely data driven. This Core will provide access to and analysis of public and project generated data as it relates to aging and cellular senescence. To do this, we will combine biostatistics, data management and bioinformatic analysis to enable generation and testing of new hypotheses.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Program Projects (P01)
Project #
Application #
Study Section
Special Emphasis Panel (ZAG1-ZIJ-2)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Mayo Clinic, Rochester
United States
Zip Code
Comisford, Ross; Lubbers, Ellen R; Householder, Lara A et al. (2016) Growth Hormone Receptor Antagonist Transgenic Mice Have Increased Subcutaneous Adipose Tissue Mass, Altered Glucose Homeostasis and No Change in White Adipose Tissue Cellular Senescence. Gerontology 62:163-72
Xu, Ming; Tchkonia, Tamar; Kirkland, James L (2016) Perspective: Targeting the JAK/STAT pathway to fight age-related dysfunction. Pharmacol Res 111:152-4
Baker, Darren J; Childs, Bennett G; Durik, Matej et al. (2016) Naturally occurring p16(Ink4a)-positive cells shorten healthy lifespan. Nature 530:184-9
Palmer, Allyson K; Kirkland, James L (2016) Aging and adipose tissue: potential interventions for diabetes and regenerative medicine. Exp Gerontol 86:97-105
Schafer, Marissa J; White, Thomas A; Evans, Glenda et al. (2016) Exercise Prevents Diet-Induced Cellular Senescence in Adipose Tissue. Diabetes 65:1606-15
Kirkland, James L (2016) Translating the Science of Aging into Therapeutic Interventions. Cold Spring Harb Perspect Med 6:a025908
Ye, Hong; Wang, Xiaofang; Sussman, Caroline R et al. (2016) Modulation of Polycystic Kidney Disease Severity by Phosphodiesterase 1 and 3 Subfamilies. J Am Soc Nephrol 27:1312-20
Huffman, Derek M; Schafer, Marissa J; LeBrasseur, Nathan K (2016) Energetic interventions for healthspan and resiliency with aging. Exp Gerontol 86:73-83
Zhu, Yi; Tchkonia, Tamara; Fuhrmann-Stroissnigg, Heike et al. (2016) Identification of a novel senolytic agent, navitoclax, targeting the Bcl-2 family of anti-apoptotic factors. Aging Cell 15:428-35
Xu, Ming; Palmer, Allyson K; Ding, Husheng et al. (2015) Targeting senescent cells enhances adipogenesis and metabolic function in old age. Elife 4:e12997

Showing the most recent 10 out of 44 publications