At the Glenn Center For Quantitative Aging Research at Princeton University we develop novel methods and technologies to innovate in aging research. We are taking a collaborative approach to probe the aging process in novel ways, thus enabling new insights in the field.

Our work spans across multiple scientific disciplines, including Mechanical Engineering (Dr. Howard Stone), Genomics (Dr. Coleen Murphy), Molecular Biology (Dr. Zemer Gitai), Neuroscience (Dr. Mala Murthy), Physics (Dr. Josh Shaevitz), and Computer Science (Olga Troyanskaya). The Glenn Center Director, Dr. Coleen Murphy, will serve as the hub of the interaction network, working with all of the investigators to apply their area of expertise to the field of aging.

• Dr. Murphy has laid the groundwork to characterize longevity and reproductive aging on a large scale, in preparation for high-throughput genetic and chemical screens. The Murphy lab has implemented a fully functional imaging robot prototype for high-throughput imaging analysis. They are designing a new large-array microscope to scale up these life span and reproductive span assays. Image analysis is a critical aspect in such high-throughput analyses.
• In collaboration with Dr. Zemer Gitai’s lab (Molecular Biology), they will develop new methods for additional high-throughput phenotypic measurements and image analysis. 
• Dr. Howard Stone (Mechanical Engineering) is an expert in microfluidics, and in collaboration with the Murphy lab (Molecular Biology/Genomics) is designing microfluidic devices to test worms’ memory and to measure neuronal activity. 
• Dr. Mala Murthy (Mol Bio/Princeton Neuroscience Institute) will lead the Drosophila studies of changes in age-related changes in sensory processing and perception. Her lab will also carry out genomics experiments to characterize gene expression in neuronal tissue relevant to the aging process.  
• With Dr. Josh Shaevitz (Physics/LSI), we will be carrying out quantitative, multifactorial analyses of behavioral decline with age using Drosophila as a model system, and will compare these declines with those we have observed in C. elegans. 
• Dr. Olga Troyanskaya (Computer Science/LSI) will apply her state-of-the-art data analysis methods to the data generated through these high-throughput experiments.