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Tau Computer Algorithm Identifies 'aging Genes'

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Image of the structure of a strand of DNA.

Researchers have developed an algorithm that helps to identify genes that can be turned off to mitigate the effects of aging.

Credit: Tel Aviv University

Researchers at Tel Aviv and Bar-Ilan universities have developed an algorithm that predicts which genes can be turned off to fight aging. The researchers aim to manipulate genes to have the same effect as calorie restriction, which has a proven anti-aging effect.

"Our algorithm is the first in our field to look for drug targets not to kill cells, but to transform them from a diseased state into a healthy one," says Tel Aviv doctoral student Keren Yizhak.

Genome-scale metabolic modeling (GSMM) is an emerging area of research that uses mathematical equations and computers to describe metabolic processes in cells. Researchers can then easily test individual models, rather than conducting traditionally labor-intensive tests.

The metabolic transformation algorithm uses information about any two metabolic states to forecast the environmental or genetic changes required to go from one state to the other.

Yizhak used her algorithm to predict genes that can be turned off to make the gene expression of old yeast look like that of young yeast. After pinpointing and testing seven genes, the researchers found that turning off two specific genes in actual yeast significantly extends the yeast's lifespan.

The research could lead to the development of gene-targeting drugs that extend human lifespans.

From Tel Aviv University
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