Can machine learning design living organisms?

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Machine learning is advancing in the field of artificial protein design, particularly through the use of Boltzmann machine learning to create enzymes like chorismate mutase with evolutionary constraints. However, significant challenges remain before machine learning can design living organisms. The complexity of biological systems introduces flaws through trial and error, which are essential for stability. Current limitations include incomplete data on DNA and enzyme interactions, as well as the need to consider allosteric regulations and potential weaknesses in enzyme design. The discussion highlights that, despite progress, the ability to replicate complex organisms remains a distant goal, with many unknowns still to be addressed in biological systems.
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Controlling evolution with data.
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My Dad was a Reliability Engineer for Boeing, Lockheed, etc. and couldn't understand Software Reliability Engineering. Software is just a mathematical algorithm that is either works or it doesn't. Problem with complex interactions is there will always be some flaw, somewhere. "The law of unintended consequences." Many of the "flaws" in biological systems happen through trial and error, and are crucial for the feedback that keeps the system stable. At the rate of DNA and enzyme discovery you would be using incomplete data. You would have to build your enzymes in accordance with current allosreic regulation and make sure your enzyme has no fatal allosteric weakness. And we need to take into account the multiple interactions we still don't know about for each enzyme. SARS has only 8 simple genes on a single strand, and we don't even yet know how it works let alone duplicate it. Still Science Fiction for the near future.
 
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