To chime in quickly: I too would be very pessimistic about the business of bioinformatics (which is different than the profession of bioinformatics!). Many of the same arguments Joann is making were made in the go-go years of the first genome wave, and lots of companies were founded either directly around bioinformatics or selling databases where specialized bioinformatics added big value. Many of those companies are either completely evaporated (e.g. Pangea), shifted out of bioinformatics (e.g. Compugen), or merged into somewhere else -- and those somewhere elses often seem to be hanging on by their fingernails. There are a few successes, but very few.
One problem was identified by Anthony -- there is just too much risk that open source projects will eat your lunch. It's challenging to compete with free. Even if you can build & sustain a superior product, a lot of potential customers are going to go with free, figuring that the delta between the two is better spent on something else. There's also the problems that the goalposts not only drift forward, but sometimes lurch sideways. If you look at Microsoft Office from a decade ago, it's pretty recognizable as the ancestor of today's Office. If you look at the big bioinformatics problems of a decade ago, they have similar themes (genome assembly, RNA->genome alignment), but the algorithmic landscape is totally different due to the sequencing technology shift. There's a lot less infrastructure you can recycle.
One last comment: I'm surprised by the remark that there hasn't been much activity in subsetting the genome for 2nd gen sequencing. There's been at least a dozen papers in the last few years with several different technologies, and most of those papers are probably in the last 6 months. By my count there are five vendors offering technology in that space. While the push for even more productive sequencer runs will continue to drive down the cost of doing a genome, these selection methods will still have utility for processing large numbers of samples.
One problem was identified by Anthony -- there is just too much risk that open source projects will eat your lunch. It's challenging to compete with free. Even if you can build & sustain a superior product, a lot of potential customers are going to go with free, figuring that the delta between the two is better spent on something else. There's also the problems that the goalposts not only drift forward, but sometimes lurch sideways. If you look at Microsoft Office from a decade ago, it's pretty recognizable as the ancestor of today's Office. If you look at the big bioinformatics problems of a decade ago, they have similar themes (genome assembly, RNA->genome alignment), but the algorithmic landscape is totally different due to the sequencing technology shift. There's a lot less infrastructure you can recycle.
One last comment: I'm surprised by the remark that there hasn't been much activity in subsetting the genome for 2nd gen sequencing. There's been at least a dozen papers in the last few years with several different technologies, and most of those papers are probably in the last 6 months. By my count there are five vendors offering technology in that space. While the push for even more productive sequencer runs will continue to drive down the cost of doing a genome, these selection methods will still have utility for processing large numbers of samples.
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