Consumption -> energy use -> global warming -> worse droughts -> desalinization -> energy use ->->-> This is a very poor long term solution

Just to clarify. Lab experiences = building recombinant DNA constructs, making transgenic organisms, using $500k microscopes, taking advantage of staffed greenhouses and animal facilities. No amount of online simulation can come anywhere close to replicating time spent in a real research lab.

I teach Biology at a small prestigious liberal arts college. My students do their real learning in the laboratories associated with each course and in their independent research projects. Their research projects often run for more than a year and include full time summer research experiences - it is an apprenticeship. This is where they learn to be Biologists and where they get the value out of the college. No amount of book learning or seminar participation can prepare them for the challenges of actually doing science. Growing living organisms, troubleshooting experimental protocols, interpreting data, and having to write and talk about their results (which are rarely 'clean') gives them the skills to make discoveries which will drive technology forward.

"a human corporation called ISDN retaliates against the boppers by infecting them with a genetically modified organism called chipmold. The artificial disease succeeds in killing off the boppers, but when it infects the boppers' outer coating, a kind of smart plastic known as flickercladding, it creates a new race of intelligent symbiotes known as moldies " - from Rucy Rucker's Ware Tetrology series (http://en.wikipedia.org/wiki/Ware_Tetralogy). Notably, this set of three books was released free by the author (http://www.rudyrucker.com/wares/).

Note she was cited for speeding and a second violation. Wearing Glass was the third violation on the image of the ticket she posts. Speeding while distracted by a web enabled heads up display - how bad would she have felt if she'd killed someone.....

When Obama was re-elected there was a whole string of articles in the press (and associated Slashdot discussions) of how good the technical team who built his campaign infrastructure was. I keep thinking that it is a shame that he did/could not hire the same people to make the health care marketplace work well. It's nearly as if the same contractors who produced ORCA for Mitt Romney got hired to bring about this fiasco. So educate me - is the health care marketplace system much more complicated than the election system? And if not was there a compelling reason to go with large contractors vs. the smart guys from the election team with a demonstrated track record?

It always amazes me that people worry so much about moving one or two genes around in plants in a thought out and carefully controlled manner yet they hardly worry about the introduction of whole functional genomes (i.e. invasive species) into ecosystems. Given the clear and deleterious impacts of introduced species (as opposed to those for GMOs which are debatable at best) you would think there would be large organizations of anti-introduced genome activists.

Trust me - benefits cost a lot more than $300 a month. The benefits that I pay for my $35k entry level employee add up to about $14k per year on top of the salary - and about half of that scales linearly with salary. Benefits include retirement (10% of salary), health insurance (>$300 a month even for an individual if you're providing decent insurance), contributions to social security and medicare, disability insurance, life insurance, unemployment insurance, and a couple of others that I am sure I'm forgetting right now. While you're obviously correct that you can buy 'benefit packages', the value of the benefits at a company that treats it's workers (even the entry level ones) well is significant. No doubt you can include these costs in consulting fees, but $300 a month it is not.

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.