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Sunday, March 24, 2019

The Efficient Mathematics of Cells

Neural nets are great simplifications of how real neurons work,  but have now been used to solve very tough computational goals.  can other examples given by nature help us as well?  I see it every day in my gardens, plants know how to seek light and water.   Converting sensing into seeking.   But are there other deeper levels of value we can adapt for our use?  A kind of learn and mimic among forms among life forms? A form of synthetic biology?  But with our own goals inserted.  Here an possible example:

The Math That Tells Cells What They Are    in Quanta Magazine

During development, cells seem to decode their fate through optimal information processing, which could hint at a more general principle of life.

'..Cells in embryos need to make their way across a “developmental landscape” to their eventual fate. New findings bear on how they may do this so efficiently....'

Adrian du Buisson for Quanta Magazine
By Jordana Cepelewicz Staff Writer

In 1891, when the German biologist Hans Driesch split two-cell sea urchin embryos in half, he found that each of the separated cells then gave rise to its own complete, albeit smaller, larva. Somehow, the halves “knew” to change their entire developmental program: At that stage, the blueprint for what they would become had apparently not yet been drawn out, at least not in ink.

Since then, scientists have been trying to understand what goes into making this blueprint, and how instructive it is. (Driesch himself, frustrated at his inability to come up with a solution, threw up his hands and left the field entirely.) It’s now known that some form of positional information makes genes variously switch on and off throughout the embryo, giving cells distinct identities based on their location. But the signals carrying that information seem to fluctuate wildly and chaotically — the opposite of what you might expect for an important guiding influence....."

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