Ciro Santilli @cirosantilli 35

Genome:

wget ftp://ftp.ncbi.nlm.nih.gov/refseq/H_sapiens/annotation/GRCh38_latest/refseq_identifiers/GRCh38_latest_genomic.fna.gz
gunzip --keep GRCh38_latest_genomic.fna.gz

This is an interesting licensing model that might just scale.

The first two that you should study are:

By cranks:

If $C$ is the change of basis matrix, then the matrix representation of a bilinear form $M$ that looked like:then the matrix in the new basis is:Sylvester's law of inertia then tells us that the number of positive, negative and 0 eigenvalues of both of those matrices is the same.

Proof: the value of a given bilinear form cannot change due to a change of basis, since the bilinear form is just a function, and does not depend on the choice of basis. The only thing that change is the matrix representation of the form. Therefore, we must have:and in the new basis:and so since:

Related:

Skew-symmetric bilinear map that is also a bilinear form.

There are several choices of electromagnetic four-potential that lead to the same physics.

E.g. thinking about the electric potential alone, you could set the zero anywhere, and everything would remain be the same.

The Lorentz gauge is just one such choice. It is however a very popular one, because it is also manifestly Lorentz invariant.

Same motivation as Galilean invariance, but relativistic version of that: we want the laws of physics to have the same form on all inertial frames, so we really want to write them in a way that is Lorentz covariant.

This is just the relativistic version of that which takes the Lorentz transformation into account instead of just the old Galilean transformation.

Two observers travel at fixed speed relative to each other. They synchronize origins at x=0 and t=0, and their spacial axes are perfectly aligned. This is a subset of the Lorentz group. TODO confirm it does not form a subgroup however.

It would be boring if we could only simulate the same condition all the time, so let's have a look at the different boundary conditions that we can apply to the cell!

We are able to alter things like the composition of the external medium, and the genome of the bacteria, which will make the bacteria behave differently.

The variant selection is a bit cumbersome as we have to use indexes instead of names, but one you know what you are doing, it is fine.

Of course, genetic modification is limited only to experimentally known protein interactions due to the intractability of computational protein folding and computational chemistry in general, solving those would bsai.