As I wrote, it still does not solve the mass of DNA required to enumerate all solution. It should be however noted, that a good solution of this particular problem is important, because as it's NP-complete, all other NP problems could be solved with cca the same complexity.

So this is a good problem, because it can be easily represented in DNA sequences and if solved, any NP algorithm could be solved using the machine solving this problem.

This is not that important as it sounds. It would not be able to solve NP-complete problems for large inputs, because it enumerates all possibilities in DNA base-pair combinations. This has actually been done before with pure DNA and their manipulation (now they use bacteria for color-marking and thus selection of the right solution's DNA sequence).

Anyways, this does not scale well, having only a few hundred cities would require DNA, that would weight cca the mass of our earth.

So this result is nice as a genetic manipulation excercise, I like that they contribute to the "standard biological components database", but it has no implication for computational complexity.

And it won't solve complex problems better than sillicon, because instead of time, you need mass. There's simply not enough material and space on this small planet for DNA solution of hamiltonian path for >500 cities.

There are lots of interesting algorithms, that are probabilistic. The definition is, that if you run it long enough, the solution will be found.

Reliability is also backed up by the times you run experiment. You can easily discard pink colours, if you get yellow, you can check the result (remember, it's NP, so checking, if the answer is okay is deterministic polynomial, i. e. fast). So filtering out the wrong solutions is not a problem.

The principial problem is, that it does not scale well. You need to enumerate all combinations in DNA. Only for a few hundred cities, you get enormous mass of DNA (earth-like weights and more).

In our country, people usually do both at once: masters and work experience. Anyways, masters is not something you would do later, that's something, you should do now. After going to work, I guarantee you, you are not going back to the university.

So go for it, the worst that could happen is that you don't finish it.

Maybe try abroad combined with some work experience.

I wrote a similiar article back in 2003 for 2600 magazine.

I copied it here to my blog right now (so you don't need to find it in paper edition of 2600 magazine):

http://jooray.soup.io/post/10105517/State-of-art-certificates-Whom-do-you

Seems nothing has changed in five years.