What do you mean 19 genes - there are only 16.

I'm currently reading 1Q84 and, like all the rest of his books, it is fantastic.

Completely true - I did not mean to make light of the storage issues that come along with big genomic data sets. The point was more that storage issues are easier to address (you can for the most part throw $$ at these issues until you get to really big data sets) than the challenges of analyzing the data which cannot necessarily be solved with brute force approaches.

We're trying to do a good job with the annotation which includes manually curating the gene families we are interested in, characterize splicing isoforms, and we're looking for genes/gene families that may be expanded or unique and provide us with insights into the evolution of the unique morphological structures we study in our critter.

Nope - the bottleneck is largely analysis. While the volume of the data is sometimes annoying in terms of not being able to attach whole data files to emails (19GB for a single 100bp flow cell lane from a HiSeq2000) it is not an intellectually hard problem to solve and it really doesn't contribute significantly to the cost of doing these experiments (compared to people's salaries). The intellectually hard problem has nothing to do with data storage. As the article states "The result is that the ability to determine DNA sequences is starting to outrun the ability of researchers to store, transmit and especially to analyze the data.". We just finished up generating and annotating a de novo transcriptome (sequences of all of the expressed genes in an organism without a reference genome). Sequencing took 5 days and cost ~$1600. Analysis is going on 4 months and has taken at least one man year at this point and there is still plenty of analysis to go.

In our Biology department we have a high end confocal microscope. This is a very expensive, sophisticated and complicated microscope with complex optical, mechanical, and control systems. The technician who services it and keeps it running was a sonar technician in a submarine for many years before he got a job working on microscopes. He is very good - logical, careful, and responsible. Obviously this is a small sample size but if his training in the navy has anything to do with his performance in his current job then this is a nice example of military training actually translating well into a civilian technology position.

$130 million dollars for 8 projects - this is truly a drop in the bucket (if it is even that much). Consider the fact that the government essentially insures nuclear plants against disasters Price Andersen act. With a disaster (3 in the past 30 years) bound to happen again in this country, and given a possible cost of a nuclear disaster in the trillion dollar range if it occurs close to a major city, $130 million dollars is peanuts. Consider the direct tax subsidies for oil exploration and extraction - in the billions of dollars per year (oil subsidies). The sad fact is that the only reason that this kind of funding is news is that our energy policy is so incredibly beholden to entrenched interests that it is a miracle that there is any funding for alternative energy sources.

Press release stories like this should get a special Slashdot category - something like scientific vaporware. While this is potentially an important discovery, none of the information needed to determine if this could ever be an energetically or economically viable way of producing hydrogen is provided. I split water into hydrogen and oxygen every day when I run gels in my lab. The energy you could potentially get from the hydrogen that this electrolysis produces is smaller than the amount of energy it takes to run the gel. Basic research is cool and all (so cool it's what I do for a living), but without more data I would guess that this discovery is very much on the basic end of the basic-->applied research spectrum. Discoveries like this are made all the time - only a tiny fraction end up being useful in real life.

That's right - new things take time to shake out. See this recent Obama speech where he makes the same point about health care reform in a pretty darn funny way.

If you read my original post you will see that I stated that "I cannot remember ever having to (directly) use calculus in the last 20 years for any of my research". The word 'directly' was used very purposefully. I do realize that the math that underlies some of the statistical and analytical tools that I use includes calculus. However, I have not had to directly deal with solving problems involving integration or derivatives for a long long time.
For example, for some of our PCR based genotyping assays, the data we produce is a melting curve (amount of double stranded DNA measured as fluorescence vs temperature). See Melting curve analysis for a reasonable explanation. To make the data easy to visualize we plot the derivative of the fluorescence vs temperature - this gives us nice peaks centered around the melting temperatures of the PCR products. To get the curves I click a button built into the real time PCR machine software - I never do the math myself. This is not to say that I could not do it (although it would take me a lot longer now than when I was in a math class and practiced this kind of thing on a regular basis).

Just trying not to be preposterous....