Information Processing does an interesting riff on the human genome, and how to quantify variations in alleles and whether clustering in allele frequence maps to morphological typing.
This is a very "physics view" of genomics, and I suspect that there will be some interesting counterpoints.
I will chicken out of the fight by claiming "more data is needed", in particular on correlations in allele variations, not just the mere fact that there is some clustering.
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From John Hawks:
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What is it with physicists thinking they can reinvent biology with a high school understanding of genetics? And, no, it's not a physics centric view of genomics. This is a pretty basic view of genomics.
Because historically it has been a very fruitful thing for physicists to do, with major subfields started in biology through importation of simple concepts and techniques from physics.
That and natural arrogance.
I don't disagree that some physicists have made contributions to biological research (the use of graph theory for modeling biological networks comes to mind). But it's important to understand what has already been done. My point was that the post you linked to was not an example of applying physics principles to genomic data. The basic concept of assignment tests to understand population structure was developed by a geneticist with a good background in mathematics.
And don't forget that statistics was invented to explain genetic data.
The blog I linked to is a physics blog.
It is the sort of thing and kind of approach that appeals to physicists and that many find interesting. Which is why I linked to it.
Actual work is, I presume, by some bio people, no idea what their background is.
I thought statistics was invented to optimise winning expectations in gambling among french gentlemen...?