Exploring the Phenotypical Landscape of Aging
Morten Scheibye-Knudsen
Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Denmark
One of the greatest challenges facing the world today is the growing proportion of elderly people in our societies. Rare premature aging disorders may be useful models to study the aging processes. We now present mechanistic data on a new premature aging disorders characterized by neurodegeneration and metabolic dysfunction. The disease was discovered through the use of machine learning algorithms such as deep neural networks on clinical and morphometric data. Utilizing in silico, in vitro and in vivo methodologies we have discovered alterations in DNA metabolism as a possible underlying cause of this disease. These findings underscore the idea that maintaining our genome may be a central tenant in our endeavor to supply healthy aging to everyone.
Financial disclosure: non.
Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Denmark
One of the greatest challenges facing the world today is the growing proportion of elderly people in our societies. Rare premature aging disorders may be useful models to study the aging processes. We now present mechanistic data on a new premature aging disorders characterized by neurodegeneration and metabolic dysfunction. The disease was discovered through the use of machine learning algorithms such as deep neural networks on clinical and morphometric data. Utilizing in silico, in vitro and in vivo methodologies we have discovered alterations in DNA metabolism as a possible underlying cause of this disease. These findings underscore the idea that maintaining our genome may be a central tenant in our endeavor to supply healthy aging to everyone.
Financial disclosure: non.
