Don't forget as well, the barrier to entry for solving cancer is non-trivial compared to the barrier to entry for creating Angry Birds. It's significantly easier to develop an app than solving cancer in terms of the equipment, research and background you need. I haven't seen many 'Learn cellular analysis in a week' books floating around.
But big problems are usually solved as a series of small problems, yes? It's unlikely that one day some researcher will combine a few chemicals in a new way and shout "Eureka! I have found the drug that cures all cancer!" A problem as complex as cancer (and diverse too: meningiomas are very different from, say, basal cell skin cancer) is something that will probably be solved by a 1,000 small breakthroughs, rather than 1 huge breakthrough. And there are a lot of apps that could help in that direction.
Here are some ideas that would be great, if someone could figure out a clever way to implement them:
1.) an app that allows the discovery of important papers that have received no attention, perhaps because they were published in journals that have low prestige
2.) an app that can detect possible bias on the part of the researchers (perhaps a tool that combines data about grants received from Big Pharma to papers that seem to prove the effectiveness of Big Pharma's drugs). At the very least this might protect some researchers from wasting time doing follow-up research based on a paper that is false.
3.) apps that offer different color encodings to DNA information to reflect different theories of the how DNA works, and how DNA damage contributes to cancer. In the same way that in Emacs you can get different color schemes for looking at your Java code, it would be useful to be able to easily format and color DNA sequences, based on the various theories regarding how non-coding segments effect the overall functioning of DNA -- this would be especially useful now, when there is as yet no dominant theory about exactly what roles certain non-coding segments play in the life of our cells.
These are 3 apps that would be helpful to researchers and which face no regulatory hurdles.
I do not offer these examples to say "We should all be working to cure cancer", though the thought is not completely unreasonable given that close to 25% of all Americans die of cancer. But rather, I offer these 3 examples simply to challenge glib assertions that programmers can't work on a problem like cancer because it is too hard -- rather, there are a million small tasks that programmers could undertake that would help the overall effort.
I agree that there are boundless opportunities for skilled developers in bioinformatics --- IF they are willing to work for free or a substantial pay cut.
The problem is that there is a big mismatch in expectations between developers and researchers: researchers are not accustomed to paying for software. Most developers in bioinformatics are other researchers, who are self-taught programmers paid by their grant funding or university, not by software sales. The quality of software is usually quite low, but it is at least free.
But I still think there is a large pool of developers out there who may work for BigCo during the day, but want to tinker on something meaningful in the evenings or weekends.
Biologists and bioinformaticians need to get better at advertising needs and harnessing the kind of community involvement that has made Linux/Apache/etc so successful.
1. Entrenched interests protecting journals: journals are not all freely available nor indexable. This isn't a software problem, it's a business and access problem. Just ask Aaron Swartz! Oh wait ...
2. Detect possible bias? There is almost ALWAYS a possible bias in drug research. You need to detect actual bias, or, as the FDA calls it, a fraudulent drug study, which involves reading the papers and so very much more.
3. Have you written DNA software? I have ... it's not easy. Plus, there are DNA manipulation tools on the market, google "dna manipulation software" this isn't an unsolved problem.
