3 ms·

This is a good point! Just for fun, for more perspective on big data, a human body generates around 1-10M new cells per second, and a cell contains about 10-10

by breck 7y ago

This is a good point! Just for fun, for more perspective on big data, a human body generates around 1-10M new cells per second, and a cell contains about 10-100GB of information. So a single human is generating 1-100PB/s of data just in the new cells! (Give or take a few OOM)

throwaway_bad 7y ago
Are you trying to quantify the "information" by the size of the DNA? I think this is a pretty meaningless number to multiply since most of the DNA will be exact copies and DNA alone doesn't capture all the information about a cell. OTOH the amount of "information" needed to perfectly simulate a cell is probably unbounded. Just a corollary of the fact that we currently don't know how to perfectly simulate reality. Even a single "real" number can take up infinite space.
- glenvdb 7y ago
  > OTOH the amount of "information" needed to perfectly simulate a cell is probably unbounded. Just a corollary of the fact that we currently don't know how to perfectly simulate reality. This is a very good point. The 'information' in a cell isn't the base pairs in its DNA, but all the atoms that make up the whole cell. And then each atom encapsulates properties such as position, velocity, charge, van der Waals radius etc. However this considers atoms with classical mechanics. In a quantum mechanical representation it would be very different again and you can start asking really hairy questions about whether information can be created or destroyed.
- breck 7y ago
  Just back of the envelope estimates if you were to do things like scRNAseq, metabolomics, genomics, etc, on every cell. Infeasible but just as a thought experiment. Most DNA is the same, but not exact, and therein lies the rub (cancer). The point on unbounded though is a good one.
- dekhn 7y ago
  It's worth reading the prior literature: Markus Covert has gotten pretty good at predicting quantitative phenotypes using whole cell simulations (with very limited cell representations, basically just feature matrices). https://www.cell.com/abstract/S0092-8674(12)00776-3 https://www.cell.com/abstract/S0092-8674(12)00776-3

by breck 7y ago

throwaway_bad 7y ago

Are you trying to quantify the "information" by the size of the DNA? I think this is a pretty meaningless number to multiply since most of the DNA will be exact copies and DNA alone doesn't capture all the information about a cell. OTOH the amount of "information" needed to perfectly simulate a cell is probably unbounded. Just a corollary of the fact that we currently don't know how to perfectly simulate reality. Even a single "real" number can take up infinite space.

glenvdb 7y ago
> OTOH the amount of "information" needed to perfectly simulate a cell is probably unbounded. Just a corollary of the fact that we currently don't know how to perfectly simulate reality. This is a very good point. The 'information' in a cell isn't the base pairs in its DNA, but all the atoms that make up the whole cell. And then each atom encapsulates properties such as position, velocity, charge, van der Waals radius etc. However this considers atoms with classical mechanics. In a quantum mechanical representation it would be very different again and you can start asking really hairy questions about whether information can be created or destroyed.
breck 7y ago
Just back of the envelope estimates if you were to do things like scRNAseq, metabolomics, genomics, etc, on every cell. Infeasible but just as a thought experiment. Most DNA is the same, but not exact, and therein lies the rub (cancer). The point on unbounded though is a good one.
dekhn 7y ago
It's worth reading the prior literature: Markus Covert has gotten pretty good at predicting quantitative phenotypes using whole cell simulations (with very limited cell representations, basically just feature matrices). https://www.cell.com/abstract/S0092-8674(12)00776-3 https://www.cell.com/abstract/S0092-8674(12)00776-3