{"id":13696,"date":"2018-06-20T16:04:24","date_gmt":"2018-06-20T14:04:24","guid":{"rendered":"https:\/\/news.embl.de\/?p=13696"},"modified":"2024-03-22T23:20:50","modified_gmt":"2024-03-22T22:20:50","slug":"new-theory-deepens-understanding-of-turing-patterns","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science\/new-theory-deepens-understanding-of-turing-patterns\/","title":{"rendered":"New insights into Turing patterns"},"content":{"rendered":"\n

A team of researchers at EMBL have expanded Alan Turing\u2019s seminal theory on how patterns are created in biological systems. This work, published on 20 June in Physical Review X<\/em>, may answer whether nature\u2019s patterns are governed by Turing\u2019s mathematical model, and could have applications in tissue engineering.<\/p>\n\n\n\n

Alan Turing sought to explain how patterns in nature arise with his 1952 theory on morphogenesis. The stripes of a zebra, the arrangement of fingers and the radial whorls in the head of a sunflower, he proposed, are all determined through a unique interaction between molecules spreading out through space and chemically interacting with each other. Turing\u2019s famous theory can be applied to various fields, from biology to astrophysics.<\/p>\n\n\n\n

Many biological patterns have been proposed to arise according to Turing\u2019s rules, but scientists have not yet been able to provide a definitive proof that these biological patterns are governed by Turing\u00b4s theory. Theoretical analysis also seemed to predict that Turing systems are intrinsically very fragile, which makes it seem unlikely that these systems should govern patterns in nature.<\/p>\n\n\n\n

Going beyond Turing\u2019s theory<\/h3>\n\n\n\n

Xavier Diego, James Sharpe and colleagues from EMBL\u2019s new site in Barcelona analysed computational evidence – gathered when they were based at the Centre for Genomic Regulation (CRG) – that Turing systems can be much more flexible than previously thought. Following this hint, the scientists, now at EMBL Barcelona, expanded Turing\u2019s original theory by using graph theory: a branch of mathematics that studies the properties of networks and makes it easier to work with complex, realistic systems. This led to the realization that network topology \u2013the structure of the feedback between the networks’ components\u2013 is what determines many fundamental properties of a Turing system. Their new topological theory provides a unifying view of many crucial properties for Turing systems that were previously not well understood and explicitly defines what is required to make a successful Turing system.<\/p>\n\n\n