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
Kandhaya-Pillai, Renuka; Miro-Mur, Francesc; Alijotas-Reig, Jaume et al. (2017) TNF?-senescence initiates a STAT-dependent positive feedback loop, leading to a sustained interferon signature, DNA damage, and cytokine secretion. Aging (Albany NY) 9:2411-2435
Stout, Michael B; Steyn, Frederik J; Jurczak, Michael J et al. (2017) 17?-Estradiol Alleviates Age-related Metabolic and Inflammatory Dysfunction in Male Mice Without Inducing Feminization. J Gerontol A Biol Sci Med Sci 72:3-15
Demaria, Marco; O'Leary, Monique N; Chang, Jianhui et al. (2017) Cellular Senescence Promotes Adverse Effects of Chemotherapy and Cancer Relapse. Cancer Discov 7:165-176
Palmer, Allyson K; Kirkland, James L (2016) Aging and adipose tissue: potential interventions for diabetes and regenerative medicine. Exp Gerontol 86:97-105
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
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 111:152-154
Schafer, Marissa J; White, Thomas A; Evans, Glenda et al. (2016) Exercise Prevents Diet-Induced Cellular Senescence in Adipose Tissue. Diabetes 65:1606-15
Baker, Darren J; Childs, Bennett G; Durik, Matej et al. (2016) Naturally occurring p16(Ink4a)-positive cells shorten healthy lifespan. Nature 530:184-9
Campisi, Judith (2016) Cellular Senescence and Lung Function during Aging. Yin and Yang. Ann Am Thorac Soc 13:S402-S406

Showing the most recent 10 out of 48 publications