Mycoplasma genitalium has less than 600 genes. We have something like 30,000. So a ballpark answer might be “at least 50 times harder”. I expect it would be very much more than that, as a free-living microbe has much simpler interactions with everything around it, while a neuron can have connections to thousands of other neurons. Neurons are also much bigger, with more physically complex stuff.
Thinking in terms of uploads, it might not be necessary to simulate all that in order to duplicate whatever is important about its function. If you don’t know what is important about its function, then you may have to brute-force it at the highest level of detail you can manage, at least until you discover what is important.
ETA: Also, neurons are faster. The time step of their simulation was 1 second. For neurons transmitting electrical signals, you’d need somewhere below 1 millisecond resolution. So there’s another factor of at least 1000.
So a ballpark answer might be “at least 50 times harder”.
The “at least” part seems wrong to me. Cellular differentiation works by deactivating some genes more-or-less permanently and by sequestering deactivated genes in densely packed regions of chromatin that are inaccessible to transcription complexes. (This is a one-sentence summary of an absurdly complex biological process. You have been warned.) Understanding the functional molecular biology of a highly differentiated cell type like a neuron won’t require the understanding of 30K interacting genes.
I don’t know if this is at all accurate, but I might expect genes to add complexity non-linearly; like each new gene gives four new possibilities, so 50 times as many genes would make the simulation up to 4^50 times as hard.
How much harder would it be to simulate various human brain cells?
Mycoplasma genitalium has less than 600 genes. We have something like 30,000. So a ballpark answer might be “at least 50 times harder”. I expect it would be very much more than that, as a free-living microbe has much simpler interactions with everything around it, while a neuron can have connections to thousands of other neurons. Neurons are also much bigger, with more physically complex stuff.
Thinking in terms of uploads, it might not be necessary to simulate all that in order to duplicate whatever is important about its function. If you don’t know what is important about its function, then you may have to brute-force it at the highest level of detail you can manage, at least until you discover what is important.
ETA: Also, neurons are faster. The time step of their simulation was 1 second. For neurons transmitting electrical signals, you’d need somewhere below 1 millisecond resolution. So there’s another factor of at least 1000.
The “at least” part seems wrong to me. Cellular differentiation works by deactivating some genes more-or-less permanently and by sequestering deactivated genes in densely packed regions of chromatin that are inaccessible to transcription complexes. (This is a one-sentence summary of an absurdly complex biological process. You have been warned.) Understanding the functional molecular biology of a highly differentiated cell type like a neuron won’t require the understanding of 30K interacting genes.
Good point. Is anything known about what proportion of genes might be turned off in a differentiated cell?
Lots, but not by me at this time.
I don’t know if this is at all accurate, but I might expect genes to add complexity non-linearly; like each new gene gives four new possibilities, so 50 times as many genes would make the simulation up to 4^50 times as hard.
I don’t think that works. It would have Mycoplasma genitalium’s 525 genes making it 4^525 times as hard to simulate as water.
I agree that when I think about the number 4^525 I don’t think it is reasonable for describing anything ever.