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 (02))
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Mayo Clinic, Rochester
United States
Zip Code
van Deursen, Jan M (2014) The role of senescent cells in ageing. Nature 509:439-46
Campisi, Judith; Robert, Ladislas (2014) Cell senescence: role in aging and age-related diseases. Interdiscip Top Gerontol 39:45-61
Escande, Carlos; Nin, Veronica; Pirtskhalava, Tamar et al. (2014) Deleted in Breast Cancer 1 regulates cellular senescence during obesity. Aging Cell 13:951-3
Campisi, Judith (2014) Cell biology: The beginning of the end. Nature 505:35-6
Zhu, Yi; Armstrong, Jacqueline L; Tchkonia, Tamara et al. (2014) Cellular senescence and the senescent secretory phenotype in age-related chronic diseases. Curr Opin Clin Nutr Metab Care 17:324-8
Stout, Michael B; Tchkonia, Tamara; Pirtskhalava, Tamar et al. (2014) Growth hormone action predicts age-related white adipose tissue dysfunction and senescent cell burden in mice. Aging (Albany NY) 6:575-86
Childs, Bennett G; Baker, Darren J; Kirkland, James L et al. (2014) Senescence and apoptosis: dueling or complementary cell fates? EMBO Rep 15:1139-53
Tchkonia, Tamara; Thomou, Thomas; Zhu, Yi et al. (2013) Mechanisms and metabolic implications of regional differences among fat depots. Cell Metab 17:644-56
Kirkland, James L (2013) Translating advances from the basic biology of aging into clinical application. Exp Gerontol 48:1-5
Baker, Darren J; Weaver, Robbyn L; van Deursen, Jan M (2013) p21 both attenuates and drives senescence and aging in BubR1 progeroid mice. Cell Rep 3:1164-74

Showing the most recent 10 out of 13 publications