While I absolutely agree with the need for cheaper way to obtain data, I don't think this is the major problem we're going to face. We now have ways of obtaini

While I absolutely agree with the need for cheaper way to obtain data, I don't think this is the major problem we're going to face. We now have ways of obtaining mountains of data (RNA-chIP comes to mind, but high-speed sequencing is a big one as well), but we don't know how to process it. We end up with thousands of candidate proteins, but then someone has to go through them one by one. Things are incredibly primitive. The huge pain point coming up is our ability to process information, which is very limited. How do you deal with machine generating TBs of data/day ? I think what's lacking is a culture of automation. Physicists do it, chemists do it, but biologists still do everything "by hand", and not only is that imprecise, is also slow and costly. We also need better ways of obtaining information about other's work. When there are 1000 paper a year published on your subject, how do you filter ? How do you even find the time to read papers in other subjects, which could be interesting in their methods, or just for general intuition and knowledge ? What we need is good algorithms, able to replace curate our sources of information well, and machines able to do the bulk-processing now needed in biology. Some things are coming up (I'm co-founding a start-up to do exactly this), but it should have happened 10 years ago.