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I'm a little surprised there's not a complete toolchain for DNA by now, including assemblers, compilers and linkers, given that the human genome project was com

by csense 6y ago

I'm a little surprised there's not a complete toolchain for DNA by now, including assemblers, compilers and linkers, given that the human genome project was completed decades ago. You still need living things for the runtime, but hasn't AlphaFold basically solved that problem too? Programming in DNA is like programming in assembly language, but a 7.5 KB assembly language program is well within the reach of a lot of people. Has anyone tried to write a 7.5 KB living thing or DNA-based tool from scratch? It doesn't necessarily even need to reproduce to be revolutionary, tiny genetically engineered transistors or structural fibers or chemical reactors might all be super useful and have super simple DNA programs that only have a few dozen lines of code. What makes this so hard?

mattalex 6y ago
The issue is the overall complexity and untestability of such a system: The (human) organism is very very complex and we don't have a model that accurately describes it in its entirety or even sufficiently enough to do any kind of complex testing. This means that we instead look at the part of the organism that is usefull and we can reasonably model. Systems like AlphaFold2 only solve a tiny tiny part of the problem (i.e. the question "given this amino Acid sequence: how does this Protein look like in 3d"), but it doesn't adress any of the other problems (like: "how does X structure behave in Y environment", "how are the interactions between these N Protein structures", "How do Proteins form complexes?", "how do proteins interact with RNA?", "How do you determine the location of Amino Acid side-chains?" and, most importantly, "what does X do?" ) I liken this to the problems we have in automatic theorem proving: We have formal logics/Type theories that allow for automatic theorem proving, but we still need computer scientists or mathmaticians even for sometimes very trivially complex tasks, because the scale of the problems is way to big to handle automatically. My AI-professor framed it like this "If you have a problem that would take you 10 minutes to solve, a theorem prover will solve it in 50ms. If you have a problem that takes you 20 minutes, the theorem prover won't solve it". We are at a similar, if not worse position, in Biology: We don't even know the system we're working in, yet.

by csense 6y ago

mattalex 6y ago

The issue is the overall complexity and untestability of such a system: The (human) organism is very very complex and we don't have a model that accurately describes it in its entirety or even sufficiently enough to do any kind of complex testing. This means that we instead look at the part of the organism that is usefull and we can reasonably model. Systems like AlphaFold2 only solve a tiny tiny part of the problem (i.e. the question "given this amino Acid sequence: how does this Protein look like in 3d"), but it doesn't adress any of the other problems (like: "how does X structure behave in Y environment", "how are the interactions between these N Protein structures", "How do Proteins form complexes?", "how do proteins interact with RNA?", "How do you determine the location of Amino Acid side-chains?" and, most importantly, "what does X do?" ) I liken this to the problems we have in automatic theorem proving: We have formal logics/Type theories that allow for automatic theorem proving, but we still need computer scientists or mathmaticians even for sometimes very trivially complex tasks, because the scale of the problems is way to big to handle automatically. My AI-professor framed it like this "If you have a problem that would take you 10 minutes to solve, a theorem prover will solve it in 50ms. If you have a problem that takes you 20 minutes, the theorem prover won't solve it". We are at a similar, if not worse position, in Biology: We don't even know the system we're working in, yet.