It features videos of alpacas while child sing about the grass mud horse, but the difference in tones between “Grass mud horse” and “Fuck your mother” is just a subtle tonal change. Since song tones override speaking tones in Chinese, it’s a sweet choir of children singing “Fuck your mother.” They sound very sweet. The alpacas are fluffy, but slightly creepy.

Definitely best misheard lyrics since “wrapped up like a douche bag in the middle of the night”

This video is coming to represent the fight against censorship. If you type in obscene or politically sensitive words often the software or the server will bounce you to an error message, so people use puns and slight changes in language to defeat the software, but everyone knows what you’re really talking about. This is very like how people got around filtering in Napster oh so long ago now.

There’s another older meme about a rivercrab wearing three watches. (Ethan mentioned this last year.) It’s another homonym pun. It’s a play on two government mottos: the “harmonious society” and the “three represents.” Harmonious becomes rivercrab, and three represents becomes wear three watches. A rivercrab wearing three watches seems to be a bit about going along with the government plans.

So now there’s an intellectual discussion going on about the rivercrabs versus the alpacas.

Rebecca shows a video for a song about the fight. The song goes between folk and rap, and talks about the river crab invading the alpaca sheep’s territory and making it hard for the alpaca to live. This is how the Chinese are talking: indirectly through these videos and essays.

It’s a mistake to think that this is a question of Government vs. Internet. The Chinese government is learning how to use the internet well to promote itself and clarify things, and even solicit speech. The prime minister had a two-hour show answering questions– sometimes very human, personal ones. The public response was positive, the government figures became more relatable. The Chinese media claim that China is using the internet to become more democratic. There’s more e-government webstuff available: they even recently took policy suggestions online. There were comments on a government run website on how to fight corruption, and even a conversation about ending the one child policy in the forums.

But don’t mistake this for Chinese internet glasnost: Rebecca points out several activists in jail for trying to organize or speak on the Internet. The government isn’t willing to take it the whole way. Instead this is “authoritarian deliberation,” where there’s a lot of public discussion about policy, but there’s no real recourse to power or protections for the people.

China also has a strong cyber-nationalism. Last year there was a big backlash against western coverage of a Chinese crackdown on tibet–Chinese students protesting what they saw as slanted western coverage. There’s a huge argument going on between China, kind of a conversational civil war online about where China should be going.

The web and IT world is creating an opaque layer between the government and the people that favors the government. There’s the Great Firewall of China, and self-censoring companies. Self-censorship takes many forms–Google.cn shows you Tiananmen square and the Nanjing massacre of WWII if you google Tiananmen massacre, whereas Baidu shows you nothing at all.

While we think of this with China, in fact this layer of companies and technologies with excessive government influence is actually global. The globalnetworkinitiative.org is an initiative of ideas on what companies should do to be a transparent layer between people and governments.

To tie it back to the history of dead white guys: the Hamiltonians vs Jeffersonians–this is the same debate we’re having between control and freedom all over the world. Do we lock up the internet for our safety or keep is free for civil liberties?

Which side are you helping? The river crab or the alpaca?

Starting out with what we have now:

Online data isn’t disconnected documents, but a network, with links between docs and the key information is the links. Folks like Google have obviously exploited that network technology. Online social networks, networks of people, the relationships being the important part. – looking at Facebook, but also affinity networks like Amazon recommendations.

The issue is using some real world activity to build networks. What can you tell about a place by what it’s connected to? They’re using mobile location data passively – but it’s messy and hard by comparison to online data. Should Facebook be able to build my friend network by seeing our phones cluster? (That will put a damper on my extramarital affairs.)

We already have smarts in online data: collaborative filtering, marketing, advertising, search, social recommendation – the next step is pulling that out of location data.

They’ve been collecting location data from taxis, blackberries and iphones

An example of what can be found:

In SF – commuting into the financial district for work. When people come into work correlated with the Dow Jones, when the stock market started going down people rolled into work later.

How much are people in SF going out at night? How late are people staying out? Night life goes way down with the economic downturn, in fact gps is down over 30% in general in San Francisco now.

The app: citysense.com: Where is everyone? How is sf right now? They can show you a heat map of iphone or blackberry to get a feeling how active the world out there is-
this brings the ability one has in a small community to tell if something is going on to a scaled up urban area. Go towards the red dots!

You can search for bars and restaurants in ranked order in how active they are. They have a buddy finder: kind of like a Google latitude.

In the next step, citysense 2.0 they are color coding the dots to find people like you. Each color represents a different ‘tribe’ – orange is the young edgies, light blue the business traveller, for instance. The citysense app determines what crowd you’re in – this is the ‘secret sauce’ – tehy’ree going to try and build a social network out of the location data. It’s honest in a way Facebook isn’t, because you co-locate with your friends. Both actual colocation and behavioral colocation- if you go to the same kind of place at the same kind of time, that’s a semantic relaitonship.

They start by building a network of places- like google meta data but for physical locations. For every possible place or street corner they’re looking to find is place a similar to place b? Some of this can be got from gov databases, and some from flow analysis. Similar to page rank… if people come to a place from similar types of origins, then leave to similar places later, they can extract that as meta data about the place. eg bankers leave the Financial District, go to an Italian restaurant then go to a similar neighborhood for the night.

They color code bars by the similar inflow and outflow, so they make them semantically adjacent. They are working with an advertising company to change how they target their beer ads.

Then to the poeple: they translate the gps trails of users into flows. As in, what are the odds of finding person of demographic 2 in commercial sector 3, which is fine dining, at 6pm on saturdays: 52%

Measure them not where they live, but where they hang out on average as a probability. They then toss out the actual location data and only keep the matrix. The matrix light up quickly because we all follow very normal weekly routines. (The Dopplr crowd must look super strange to them)

They have 4 million users – with semantic data relationships being the social network.

They identify tribes based on advertising applications:
young and edgy: poor, more ethnically diverse
weekend mole- out occasionally on weekdays, Latino, middle income neighborhood
mature homebody – rarely goes out

This is to help companies better target their ads.

They’ve had to do interesting re-calibrations recently. Usually the season requires re-calibration, but the economy has caused massive changes.

They’re interested in the next network: it’s not the online network, it’s the offline world.

Greg was a firehose, forgive my errors and omissions.

DC is like a university with a really massive ROTC program. If the internet is ethernet, congress is token ring. One person speaks at a time, for instance. Once Greg saw more than 10 minutes for a roll call vote–no electronic anything. Congress paper based–so it’s not exactly version managable the way people want to stick bills in Subversion, that kind of thing.

Important to realize that Legal code != Software code
Legal is intentionally fuzzy rather than rigorously logical–it’s good that way.

It’s really not like what programmers are used to. One of the bills going through the Senate during the banking crisis changed a medical benefits bill, turned it into the Emergency Economic Stabilization bill. It would be like a quick patch of your word processor that turned it into a database.

Government doesn’t have legacy systems, it *is* a legacy system. It’s an application designed for one user at a time–the elected official is that one user. Each rep represents around 600k people.

The Executive branch does most of the heavy lifting of government.

Think of every agency as its own enterprise. There’s a total $71 billion IT for the Executive.
More then 30% of the civilian work force in the Exec are retiring–real opportunities for change there.

The US Government suffers from being a first adopter, which is why it is so outdated–like the NY subway, suffers from all the first mover problems. Things are strange and falling apart and patched together because so many things came online before the current situation.

Greg shows us Procurement for the DOD–ridiculously complex graph. Ridiculously complex is the overwhelming theme here.

This is a pre hoc world in gov–the commitments are long term, and logistics are *hard*. You can’t fork a highway. For instance, GSA is working on their 2011 budgets.

There are lots of not government but related people in DC–think tanks, non-profits, lobbyists, FACA advisors (the formal advice channel- 75k individuals with expertise that interact with the 1300 gov agencies.) You don’t actually want to let people provide advise for free, in order to prevent the conflicts of interest, hence FACA.

Sunlight tracks contributions, example on the repealers of the Glass Steagall act on how much they got from financial sector (but correlation is not causation).

The initial bailout was 3 pages, asked for 700 billion, and asked for no review or oversight. (This is actually not uncommon, in order to prevent congressional micromanagement. Obviously it was not a good idea in this case.)

Gred shows a map dotted with blue–they are earmarks from a particular bill can stretch everywhere, sweetening the deal gets people to play together. In this case reps in congress.

Government actually works, an example:

1970s: The External Financial Reporting Act comes into being and congress sets up Congressional Budget Office. (Under Nixon)

1980s: We get Federal Managers Financial Integrity Act and consolidated reporting.

1990: Chief Financial Officer Act & Government Manage Reform Act (Both under Bush 1)
We get FAADS, FDS – every government contract for more than 25K has to be reported into the FPDS- nice, but a cobol data file, and every transaction has 120 field associated. Ouch!

2000: Bush passes the E-Gov act and the FFATA act–required an end user searchable interface on FPDS: usspending.gov
Also check out et.gov: emerging technology . gov.

This isn’t bad for a system that only gets new ideas every four to eight years.

Why mr hacker went to Washington: 9/11
The tools we are used to for information sharing didn’t exist back then. He was in NY and trying to help out. We had no ad hoc systems we could stand up to track anything, requests social networks, etc.

By 2008 there’s a new form of mass participation. Huge number of Obama house parties mapped on google earth.
Recovery.gov, all the other agencies has to do .gov/recovery. firct time there’s webpage interagency communication. all happened in one month.

Even GOP has an rfp out

Sunlight is building a data commons, check out the Apps for America Contest, 15k price by march 31, just build things with their apis

Things Greg is seeing:
* Creating alternatives that force government to adopt another model
* Public means online
* Human *and* machine readable
* Timeliness

Greg ends with a picture: “the arrival of transparency” graphic from the New York Times. (Hint: it goes up recently :)

Synth bio is the idea that biology is a technology to engineer novel systems- say drugs, biofuels, other sexy sexy projects.

This is to be a flavor of what engineering biology is all about.

We will be installing a program into E coli to make it turn red, glow in the dark, or smell like bananas… We get to pick!

The DNA is stapled to the pages that describe them in the notebook.

Some of the tools of synth bio: biobricks, interchangeable components that can be strung together into programs. The parts registry lets you snap programs together.

iGem participants get a kit in the mail and pick out parts and mix and match them into new programs they want- much like the one we’re holding. The Scottish team made and E coli that turned red in response to arsenic contamination.

Standardized interchangeable components are limited, but let a lot more people get involved and democratizes access to the tools. This is still biology- it can seem kind of scary- do you trust your neighbor to engineer biology?

Question from the audience: how do you prevent the terrorists from building smallpox?
Answer: You can’t perfectly. “How do you prevent a car bomb from blowing up outside?” You don’t, but you can limit it, and create a community that self polices.

Question from the audience: What about release? Would the arsenic detector be scattered on the ground?
Answer: We don’t understand how manufactured organisms will interact with the environment. We work with safe organisms, and we don’t release our stuff. These E coli are pretty innocuous, so we’re going to wash our hands before lunch.

It’s pretty unlikely that anyone is going to make anything in a lab that’s dangerous right now, but we should think about that.

It’s a bit legally gray, the guidelines everyone follows are only required for people receiving NIH funding, and there’s some places with local laws (like Cambridge) … There’s no clear answer.

We’re punching out our DNA and dropping it in cells. (Ben has returned our vial, #19 and #10 to ice, while the receptive cells take up our dna)

We’re installing on a plasmid. “You’re literally just mixing the plasmid DNA with the cells.” These cells are competent, which means they can take up DNA easily. We cool the DNA, then do a heat shot- then shock it in a 42 degree water bath for 30 seconds, time it, put it back on ice for two minutes. We’re disrupting the membrane of the cells and letting them recover. Then we’re adding media, food for the cells. Then we’re incubating them with our bodies. I’m going to keep mine in my armpit, I think.

Can’t mix the three bit of dna, because they’re the same plasmid – they are ampecillin resistance plasmid, so there’s a space collision, things aren’t likely to play well together.

DIYbio.org is a good place to learn about good lab practices.

I am now heading to lunch, incubating a tube of e coli in each armpit. (Will update with pictures after lunch)

Update: I’ve now transferred my E. coli to a petri dish and a vial, freeing my arms.

…and no, I was in a hurry, and I didn’t wash my hands before lunch. Phear my bad lab skillz. (& Know your organisms.)

“Biology is a technology for manufacturing,” says Drew Endy. Engineered genes could remake mass-production and materials. Cells are proven nanotechnology with a history of creating large-scale output. Look around the room, anything manufactured or grown could very well be produced more efficiently in a cell. From impact resistant plastics to water proof fabrics or moisturizing cosmetics — it could very well make the most financial sense to design an organism that cooks up what you want in almost any existing manufacturing industry.

All of this is still a ways away. A genetic engineering job today requires a Ph.D in a subject like molecular biology. Often postdoc work is on the job description, experience working directly with genetic sequences, and amazingly comprehensive knowledge of a number of organisms … and, of course, the ability to be a team player. Genetic engineering is a boutique field. High status, highly trained specialists create changes out of the ATGC’s each time they are needed to serve specific business goals. “Imagine if you had to build a mechanical device, or a computer, and your work started with the refinining of ores to produce raw materials, and then next the processing of these materials into custom components, that you eventually assembled to produce a perhaps working system. That’s what genetic engineering is like today,” explains Endy.

Also: Dr. Endy wraps up on the impact of synthetic biology. (mp3, 5.1m)

Hackers and tinkerers are neither patient nor team players by definition. What they make reflects this fundamental difference. It took Bell Labs to bring us UNIX and the world we live in now. It took Linus Torvalds to bring us a happy fat penguin, and Google, the OLPC, and IBM as we now know it. What comes out of garages is different from what comes out of office parks, though they build and co-contaminate each other continuously. Thusfar, biology has been locked in office parks, bereft of its other half. Without ever finding out what it might have gained, the business side is likely to try to hobble the dabbler, the hacker, or the independent.

The question is not so much whether synthetic biology will remake society, but who will be in control when it does. Biotech companies are stumbling over each other to file patents by the palate. Already the company that created the base pairs for Endy’s MIT classes on building Biobricks projects, Blue Heron, is locked in a patent fight in federal court with Codon Devices, the MIT spin off company in the same field. Most of the research, including university research, is going to be locked up by the tightest IP law biotech companies can manage. Consequently, Endy’s fab projects are in a race with industry interests which echos Craig Venter’s private-sector race against the Human Genome Project. Genetics will almost certainly look like software, with open, viral, and proprietary products and competing standards in the marketplace. And like software, it will be the purview of multinational companies and high school hackers.

Hackers will go farther in the pursuit of scratching their own itches and seeing what they can do than someone that has to worry about a bottom line. It’s impossible to anticipate the variety of things people will dream up in their garages. Already we have transgenic glowing fish, and there will certainly be more of the same. Like any medium, humans will express themselves in the organisms they design. One can imagine sundials with digital displays, or graffiti that must be exterminated as well as cleaned up. And certainly we will have a whole array of colorful, glowing pets.

Extraordinary opportunities for yet-unknowable creativity nearly always comes with the threat of catastrophic destruction. In biology, the downside comes up quickly. This is because un-engineered Nature has always been so good at catastrophic destruction on its own.

What happens when the bad guys start making microbes? Thoughts of malicious biology haunt the background of all the miraculous proposals. Indeed, with a little imagination, bioengineered threats could emerge from anywhere. From industrial espionage in the farming sector to massive production of illegal drugs, it’s easy to see that a world of synthetic biology will offer challenges well beyond what we can imagine now. Much of our current worry is focused on lethal pathogens, like smallpox or the 1918 flu. The later created a stir in 2005 when a group of researchers published the genome, and then recreated the virus on their own. A bit of nearly all genetic engineers’ minds seems to be chewing on the biosecurity problem. Some of the ideas being discussed are controlling access the production of genes, auditing manufactured genes for known pathogenic sequences, and creating comprehensive biosensing in the environment. All of these proposals have well understood flaws.

There is no comprehensive answer to the threats, and it’s not likely there will be. While the best minds in bioengineering are thinking a lot about these dangers, it seems likely that management of human created malicious creatures could be its own full time industry, joining our existing war with natural disease. We know we have to go forward. The cat is out of the bag — even if the good guys complete gave up genetic research, there’s no way to stop the bad guys going forward.

Also: Dr. Endy on biotech security. (mp3, 3.2m)

Next: What’s next for the microbe hackers.

Wheat Rust is courtesy stellarr on Flickr.

Three years after Tom Knight invented the first standard for hooking together genetic parts in a living programming language, the BioBricks standard, MIT put the idea to work. They started a contest for students around the world called the International Genetically Engineered Machines (iGEM) competition. Students began to make and put together parts of DNA code into repurposed organisms. Some were bacteria that smelled like bananas, some glowed red or green, one team even created a cell that built itself protein balloons. Every year the teams can build on the parts they and other students have created. Theoretically, this means next year’s iGEM winner could be a balloon-building organism that glows green and fills a room with banana scent. Today, the parts database at MIT boasts an impressive 2,500 reusable snippets of public domain DNA — all for the taking.

Stringing together many parts or devices, creates systems — those are what can sniff arsenic or take light impression like a film emulsion. They are the complex forms of many connected devices. Being student work, the quality of iGEM systems is all over the place. But once one student group has put something in the archive, anyone can see how it was done and how it was used. They can contribute novel combinations back into the archive, creating systems of DNA that still others can expand on. It’s not at a commercial level, but provides a proof of concept for a much more sophisticated archive. In the mean time Endy sees this open source genetic model as a vital key to getting people playing with DNA.

Endy refers to the students in iGem as “freeform teenage genetic poets.” He points out that what they do for fun is still a bottom line business decision in the real world of biotech. It’s clear that he’s not just trying to create an academic or business model for synthetic biology, but a full culture. Genetic artists as well as students, hobbyists, activists, researchers, and businesses are part of Endy’s future. Genetics will be social, political, mainstream, and constructive in an entirely new ways.

[Also: Dr. Endy on Biobricks, iGEM, and a new project that takes parts to the next level. (MP3 format, 3.9M)]

The success of iGEM and BioBricks led Endy and others to believe this approach, open and available parts for any and all, could have a big impact on the field of synthetic biology.

This fall, Endy plans to leave MIT for parts west. He will set up at Stanford, and work with UC Berkeley and UC San Francisco to create the big brother to MIT’s student created parts library. This ‘Bay Area Parts Fab” will be a repository of genetic code engineered by professionals and scientists at a high caliber, documented, and published openly. The Fab, envisioned as a public benefit with university support, will employ 25 genetic engineers full time to produce parts they believe will be generally useful. “A collection of parts will let you work with off the shelf components. You won’t need to be a Ph.D researcher with a laboratory in order to get stuff to work,” says Endy.

When genetic engineering started there wasn’t a lot of call for sharing with the uninitiated, and certainly not with the competition. Traditionally, one of the things that has kept genetic engineering in the hands of monied institutions is the intellectual property. Genes are often patented, that’s how pharmaceutical and biotech companies protect their investments. This model is incoherent in a world of openly available synthetic biology. Patents are expensive and cumbersome, and abstraction requires freely building on the work of others.

Endy and others are looking for an alternative to the costly and hampering patent model. The goal is to create something that can be shared with anyone doing research. Issues with this would remain if and how DNA could be used commercially, and if including a given chunk would require reuse to be licensed under a similar open license, like GPL’d software. In short, will synthetic viruses be viral? Ideas like Creative Commons copyright licensing and voluntary blanket licensing are floating in the air, still untried and untested.

Next: Synthetic biology gets mean and scary.

Photo courtesy of Mike & Amanda Knowles, via flickr.

Dr. Drew Endy’s approach to the next generation of bio technology depends on engineers, programmers, hackers, social theorists, lawyers and so forth, to inform biology. He believes we can make genetic engineering, like computers, part of every facet of our lives, changing the way humans do their business.

He seeks to put synthetic biology into the hands of the interested, not merely the professional. The potential is to widen the range of goals, to extend this emerging tool to many disciplines.

The key, says Endy, is what computer scientists call abstraction.

Fundamental to what created modern software was that idea that no one should have to type in that monotonous stuff twice. Once something was there, it should just be reused, not re-created. More important, once it was done the programmer didn’t have to know how it worked to do it again. The common wisdom became that no one should have to know how a computer worked to make it do entirely new things.

Also: Dr Endy explains Abstraction (mp3, 4.9mg) and Standards (mp3, 3.1mg) for synthetic biology.

The language of genetic engineering is out of reach for most people, but the idea of making something do what they want is not. Along with famed MIT computer engineer Tom Knight, Endy is trying to bury the DNA and its nucleotides down the same deep hole that swallowed the 1s and 0s we users never have to thinks about. To do this, they are creating standards and a vocabulary defining a DNA language for programming organisms. Assembling basic gene codes into patterns that can be strung together and reused allows people with far less sophistication than modern genetic engineers to create cells that those modern genetic engineers would never have dreamed up. This puts the power of the Ph.Ds into the hands of the rest of us, and what was a multi-million dollar research task can become a high school science fair project. This path echos the success of computers from their enormous and expensive infant stage to their penny-cheap microscopic adulthood.

Tom Knight is one of the greybeards who watched much of that process, and came to understand how the history of computers and the internet worked. Knight recognized early that to do this in biology, he’d need a reliable way to categorize bits of DNA by what they did rather than their sequence, making the syntax of the programming language. In 2001, Knight invented the first standard for creating a genetic programming language and called it BioBricks. To build with BioBrick parts, one had to learn the basics of how they hooked together and what they did. From there it was a process of building up DNA like Lego.

No one has ever done anything like this. “It might not work,” Endy freely admits. But Endy sees value even in the failure of abstraction. “The ‘worst case scenario’ for synthetic biology is that we won’t be able to build anything useful, but our failures will highlight the most relevant unknowns in biology, (what) we should figure out next.” He adds that we are already beyond that scenario, but as we go further out, more issues of society intrude on issues of science. The history of GMOs suggests the biologist should try to keep the public informed of where they might meet the biologist’s work.

Tomorrow: The legal status of genes may ultimately be even more contentious.

Dr. Drew Endy tends to fidget. He motions frantically when he’s trying to get something across. “It’s hard because we’ve never made it simple,” he explains with exasperation. Endy, a professor at MIT until the end of the school year (he’s headed to Stanford), engineers new life forms. He’s spent his life doing the hard work of bending the complexity of DNA to his will.

And he’s determined to make it simple for you.

Drew Endy is a leading star in a field that’s emerging to be the biggest thing since Walter Brooke suggested to Dustin Hoffman he should think about plastics. He’s a synthetic biologist, a group of scientists and engineers that take microbes with familiar names like E. coli and yeast and make them do previously unimagined things.

Also: Dr. Endy explains what synthetic biology is. (mp3, 5.7mg)

Synthetic biology is next-generation biotech. Over the past 30 years, genetic engineering has laid the groundwork for what synthetic biology is and will be. All the important innovations of genetic engineering are put to work with newer techniques. What makes synthetic biology more than its predecessor is the ability to write DNA cheaply and easily. After designing a sequence, the genetic engineer can mail it to a vendor that will build the base pairs and overnight it back to them.

Sequencing, or reading out DNA, was once the purview of, at the very least, grad students. Now it can be accomplished by minimally trained unskilled labor. Will DNA writing go the same way DNA reading has gone? Probably not as much, but the price of synthesizing a base pair has lowered 16 fold in the last five years according to Endy.

Synthetic biology doesn’t change the goals of biotech: medical applications, environmental remediation, biology based manufacture, etc. But it brings them closer, and adds more possibilities to the pile.

So what does a future of human-built biology look like? The obvious ideas are the ones researched now institutionally. It doesn’t take much imagination to see that a great mover in this field will be pharmaceuticals, and the medical concerns that drive the healthcare industry. We will likely see progress towards biological agents for pollution remediation, drug manufacture, and nanomaterials. Many of these are not only in the works, but on the verge of entering the market. After that, a little imagination goes a long way.

The holy grail right now is alternative fuel production. Petroleum’s supply and environmental problems might not dog an organism custom designed to get from the sun’s energy to a liquid we can stick in our vehicles. If geneticists can produce a viable replacement for petroleum, there’s a mint to be made even if the organism goes off patent in 20 years. J. Craig Venter’s institute and his company, Synthetic Genomics, are particularly geared to this goal. The institute receives its research money from the U.S. Department of Energy as well as Synthetic Genomics. It’s still a ways off. The institute has yet to complete its first fully synthetic organism of any kind, much less one that makes gas. With genes already modified to produce drugs, and the attention paid to fuel, a wide array of other products are candidates to grow instead of fabricate. Synthetic biology is very serious business.

Tremendous minds and piles of money are pouring into the potential organisms, and almost any one of them could easily payback that investment if successful. Drew Endy, despite is in-demand talents isn’t part of any of that.

What makes Drew Endy’s work unique in his field is what he wants to do with it, not the research itself. He wants to modularize DNA into something like a programming language. Then he wants to give it away.

Tomorrow: How can you make anyone a genetic engineer?

Wondering what that “Hello world” image is doing at the top of the post? It’s synthetic biology in action: Students at the University of Texas re-engineered E. coli to be photosensitive, like photographic paper. Their first message? The programmer’s traditional. It’s published here courtesy of Jeff Tabor and Randy Rettberg.