Your point about sequencing is a good one, but this is the only area of biological research clearly improving exponentially...
Without being too argumentative, I'd put the odds of increases in computer power leading to biological breakthroughs at much less than 100%! I'd be surprised if it was as much as 5-10%.
What areas of biological research are fundamentally limited by computer power? I can think of a few where more power would be nice to have, but none where that power would be transformative.
The possible exception is the example you mention---DNA sequencing--but the problem there is that the rate of growth of sequence information is greater than More's rate; slightly ironically, this field really needs computer scientists to help develop new algorithms much more than it needs computers...
But your question is specifically about computational power. Any area that requires modeling or methods that must be over-simplified in order to run on today's hardware are candidates for benefit from computational power. That seems to leave a lot of room: http://en.wikipedia.org/wiki/Modelling_biological_systems
But I will grant that development of new algorithms is also important. It's just that computational power itself assists in the discovery of new algorithms via the development of better research platforms.
Without being too argumentative, I'd put the odds of increases in computer power leading to biological breakthroughs at much less than 100%! I'd be surprised if it was as much as 5-10%.
What areas of biological research are fundamentally limited by computer power? I can think of a few where more power would be nice to have, but none where that power would be transformative.
The possible exception is the example you mention---DNA sequencing--but the problem there is that the rate of growth of sequence information is greater than More's rate; slightly ironically, this field really needs computer scientists to help develop new algorithms much more than it needs computers...