Is that actually working? I tried rolling my own neural nets and running genomic data through them and instantly realized the problem was low N, high autocorrelation in the data. Bayesian forests seem like a better choice, but that's me.
There have been some recent papers in subsets of genomics with a bit more data (Transcription factor binding, for example [1]). You're correct though, definitely depends on your problem.
