Sci Foo recap: If I were to do it all again, I'd offer up an intro to evo-devo, in particular because some of the more gung-ho genomics talks seemed so oblivious to the difficulties of the fancier projects they were saying would be in our future. I really think the organismal-form-from-DNA problem is going to make the protein folding problem look trivial, and this is especially going to be true if the DNA Mafia is going to pretend the developmental biologists don't exist. (Via Pharyngula.)
A computer science point of view makes this point easier to understand. At the genomic level, evo-devo focuses on the evolution of the switches that control gene expression spatially and temporally in development in development. To a first, discrete approximation, these switches form Boolean combinations of transcription factors (themselves the expressions of genes) that gate the expression of another gene. There are also feedbacks and delays in the system. So, we have a pretty powerful computational device, and we know that recreating (learning) such a system from its behavior is in even relatively simple cases (finite-state machines) extremely hard.
We might hope that the system is constrained in ways that make it easier to reconstruct from behavior than the worst-case results suggest. But I see no functional reason why that should be the case. "Easy to reverse engineer" doesn't seem to have an evolutionary advantage, and it may actually be disadvantageous, in that it could facilitate the evolution of parasites and other attackers. (Think of the defensive advantages of encrypted communication).