Seems pretty straightforward to me: 1) programming objects have properties and methods; 2) within cells it is probably possible to have analagous entities (perhaps various types such as molecules, organelles, etc) which have defined properties and predictable behaviours; 3) could we soon have a computer and a sufficiently comprehensive database of these objects and their behaviours for an AI to start correlating how they are combined and how they would need to act to produce a cellular effect (e.g. regenerate a damaged cell); 4) could this be speeded up with the advent of quantum computing?
thaumaturgy|3 years ago
Less flippantly: biological processes don't behave similarly to a big network of discrete objects with specific traits (methods and properties in OOP parlance). The domain of biology is composed of lots of molecules that combine to form bigger molecules that in turn get classified into hormones and proteins and amino acids and other organic compounds, and these all interact in super complex ways that are very difficult to model. For example, protein folding is a big area of research that is attempting to model the behaviors of just one set of molecules [1], and it is proving to be a really difficult problem to solve despite throwing enormous amounts of computing power at it [2].
And, we don't even know what we don't know yet in broader biological terms. It's not like we have a pretty good model for biology at macroscopic scales and we're just working out details -- this isn't civil engineering. The details that we're still missing matter a lot in how biological systems behave.
Quantum computing likewise is not a magic pill that will suddenly make all of this easier. Quantum computing is good at solving certain kinds of problems a little bit faster, but expectations for quantum computing have so far greatly outpaced its actual development.
As a side note, "systems thinking" in programmers often leads down dark dead-end alleys full of misunderstandings and wrong questions. Modern science is pretty darn advanced, and today's PhD candidates are introduced to programming as part of their education. It's usually safe to assume that if an advancement in a given field were possible through rudimentary programming, then someone would be working on it; programmers who are curious about specific fields should first start at the basics in those fields and put the time in to become familiar with them. That process will eventually lead to the right questions to ask in those fields.
[1]: "What is protein folding? A brief explanation", https://news.ycombinator.com/item?id=25261591
[2]: "Protein folding: Much more intricate than we though", https://news.ycombinator.com/item?id=25284998
Andy_G11|3 years ago
unknown|3 years ago
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