It’s a little weird now that I think about it. Despite doing tons of PCR reactions day-in and day-out at the Genspace lab for one reason or another, I never tried  to dig into what exactly DNA barcoding entails in its visceral, barcoded details. Well, recently some of our Genspace members including yours truly went out on a sort of field trip to the Harlem DNA lab (situated within a junior high school in Harlem) for a day-long DNA barcoding workshop in preparation for the upcoming NYC Urban Barcode Project.

And the process couldn’t be easier. In a nutshell it just involved amplifying specific segments of DNA from a sample organism and sending it in to Genewiz for sequencing. The specific DNA segment to be amplified differs slightly from the kind of organism (is it a fish? Plant? Or insects?) but in case of most vertebrate mammals you use a portion of its mitochondrial genome called cytochrome c oxidase subunit I (COI) as the bacoding region. Mitochondrial genome (something I’ve been working with a lot for the past few months, ironically enough) is ideal for this sort of genetic species identification since they hit the exact sweet spot between homogeneity and differentiation within similar branches of the phyla, due to their rate of mutation and how mtDNAs are only passed through the maternal line. If you’re interested in performing your own DNA barcoding experiment outside regular lab settings or any official competition you can do so with the pdf files of requisite primer sequences already online and just order it straight from places like IDT. While specific protocols for running the PCR and prepping samples differ from place to place (I’m still looking for that perfect optimized protocol) what you are doing is a basic PCR amplification of the specific part of the mitochondrial genome, so when push comes to shove I’m sure simple chelex based DNA extraction (crush and pop in the sample with chelex beads for 10 minutes at ~99 C, centrifuge at 13000rpm for about a minute and extract the supernatant) combined with primers and PCR mastermixes or GE PCR beads (which already contain pre-made taq polymerase and buffer mixtures for optimal performance) will work just as well, provided that the sample is fresh enough. I think I’m going to run some experiments with the materials we already have at the Genspace lab and post the results later on. Once we put together a library of verified barcoding primer parts we should be able to do some very interesting projects and classes with the NYC biology community at large.

During the barcoding workshop we had a chance to pick out our own samples and run through the barcoding process with the instructors. I picked regular house ants, some random plant Ellen brought from her garden, and a YFP producing zebrafish that’s been dead for some time (it’s a long story). I went through the DNA extraction, purification, and PCR process outlined briefly above, using appropriate primers (for students participating in the competition the Dolan DNA learning center & Harlem DNA lab will provide the kits for free!). Here’s a picture of the gel we ended up with, dyed with syber-green (thanks Oliver!).

Now I seem to have misplaced the list of what each lane does, but the point is, all the barcoding amplifications worked except for the transgenic zebrafish. And it’s not just me, transgenic fish samples prepared by everyone else failed as well, something I can only attribute to the condition of the sample at the time of the barcoding experiment. You see when living things die cells lose structural integrity and rupture all over the place, mixing existing DNA molecules within the cells with all kinds of junk and nucleases that will damage the sequence. Considering the fish was stinking up to the high heavens by the time we got it to the lab that certainly sounds like a very likely scenario to me.

All the other samples works beautifully, and we prepared about 10ul aliquots of each PCR product and sent it in to Genewiz to get sequenced (the same Genewiz I got my mitochondrial DNA sequence from). They’ll be getting back to use within few days with the sequence data we can feed into public databases of DNA barcodes to determine what kind of organisms they are.

People always talk about how the field of biotechnology is advancing by leaps and bounds, and how the infrastructural developments like massive DNA sequencing centers for cheap sequencing will change how most view life and themselves. For a person not previously versed in biology like myself this was a great opportunity to come face to face with capacity for people outside of traditional academia to contribute to the sciences, using largely off-the-shelf technologies and public databases. The entire process of obtaining the sample, amplifying a specific genome within the sample, and getting it sequenced probably cost me about $5 in terms of materials. Think about that. $5 dollars to gain some level of insight into a genetic makeup of an unknown organism, open to everyone. Although this is nowhere near the kind of stuff we can do with true deep sequencing the day is coming, and it will certainly make for a very interesting world.

If you’re interested in learning more about the NYC Urban Barcode Project or DNA barcoding process in general, feel free to contact me at sung at genspace dot org. Genspace is one of the sponsors of the NYC Urban Barcode Project and we are looking forward to input and participation from students and teachers around the city!

But first, let me give you a news, this is the one that got me writing on this blog again after months of vacation:

Virgin Galactic is hiring astronauts! Not just any astronaut, but a private astronaut presumably for their SpaceShipOne based launch program at Mojave spaceport.

You need all the qualifications usually associated with being hired as a pilot for any Aerospace corp, with preference given to those with real experience in spaceflight. I guess all those out of work astronauts from the space shuttle program can still get their flight on

I kept asking myself why I didn’t go to a flight school instead of bothering with all this physics baloney. I think my friend who does aeronautical engineering thinks the same way too. I was more or less blaming my own shortsightedness before I hit upon a memory from decade ago.

I wanted to go to space, become an astronaut. That meant I had to enroll in the airforce, go through the officer’s training, and get really, really lucky. Now luck part I never really had a problem with. Don’t worry about things you can’t control, as they say. But enrolling and spending my life in the military just to get to space? Man that just put me way off. It’s probably the same story with my engineer friend. And I’m not even sure what women go through when they want to become an astronaut. I’m thinking it’s something a lot more different from what males have to go through, whether we want to admit it or not.

I’m not really crazy about the idea of libertarian capitalism, but I can’t help but to welcome this development of private space industries. I think years of treating space as if it was a special military domain really killed lots of initiatives that could have happened, and just shelved decades worth of scientific progress under the guise of national security (for all nations with capacity for spaceflight, really).

Genspace is in full swing, and Ellen’s busy running her biotech crashcourse, with other group-wide projects planned out already. Who would have thought we’d actually have a functioning biotech lab in NYC two years ago? Kudos to the people who stood by us all this time. Just having a lab is not enough though, we’ll be introducing some pretty awesome projects soon, just stay tuned!

I have so many things I want to write about now that I’m finally sitting in front of a computer and logged into my blogging account… But good things need time to mature, like hot pot. So I think I’ll just write about that one thing I’m supposed to talk about in this post

So we (me and Oliver) are planning to launch a high altitude microbial sampler into the stratosphere and do metagenomic analysis of whatever the samples we can gather from there. Right now I’m thinking of about 25~30km altitude, which should be around temperature range of -50 ~ -20 degrees C, which is really cold but not quite as cold as the furthest reaches of antarctica. Just to give you a scale of how high we’re going, latest version of Boeing 747 has top service ceiling of about 13km altitude. Our device will be flying at or above the double that altitude. Here’s an interesting picture of the Earth taken around 20 km.

Now simply launching a weather balloon into the stratosphere with some minor circuits, GPS and a digital camera would be simple. In fact, if it’s all I wanted I can just walk out there and launch my own balloon-sat right now. Yet, what’s the point in doing what everybody else is already doing, am I right? Now that we have a working biology lab we need to do something to bring my love of space together with my love of biology. Which means microbiome sequencing using samples taken from the above.

You see, there’s practically no real research data on the microbiome of the high altitudes. Considering the resilience of life (if you throw bunch of fruits out into the space from ISS, they’ll survive -kind of) and interlinked atmospheric conditions of the planet as a whole, we personally find it impossible to think that the realm of high altitude is totally devoid of life. There are papers out there tracing back to the era of the cold war suggesting that the maximum height of the planetary biosphere might in fact reach far beyond conventional height, with some evidences suggesting spore presence at mesosphere (~80km).

In order to have at least modestly reliable results from our experiment however, we need to design a device that can remain sterile to and from the stratosphere that will function despite heavy shaking, blistering cold, and falling. So far we’ve been making good headway into design and building of the device (Oliver is practically a McGuyver, with PhD in molecular biology) but it’s been a whole lot tougher than simply throwing together balloons, parachute and a camera that most of these projects tend to do. I’ve accumulated some interesting resources and research results during the course of the project, and will be uploading it to the net soon so that other people can follow in our footsteps and do their own high altitude sampling as well. Maybe it would be possible to grow this into an international program of sorts, considering the nature of the kind of organisms that might be found in the stratospheric range (if we find anything at all).

Recently we launched a simple tethered balloon sat to take pictures of Brooklyn from above. The contraption really had nothing to do with the sampler we’ll be launching, but it still gave us a good feel for what the real launch in the future might feel like.

The balloons were attached to a simple digital camera, a 1.99 semi disposable that took really horrible pictures. I’ll try to find a good one or two and post it later.

We launched the balloon on top of the Genspace building. The weather condition was really great, not too much wind at all. The sunlight was beautiful as well.

I’m one of those kids who used to stay up late at night thinking about the space, the high sky where the deep blue voids split over a thin red line of the sun rising, or setting somewhere over the distant part of the planet. Really, to this day the images still have the power to stir my heart, and make me feel like a human being. This is a meager start but who knows, maybe somebody’s already working on a synthetic biology satellite design that might one day take to the skies

Now, we are talking about Genspace, and we do have a bit of reputation to maintain. So as much as I would like to recommend everyone to get cracking on the battle.net with Starcraft 2 we’ll have to make do with something different; a computer game with science in it.

It’s called Phylo, and you can find it here. Phylo is an entirely browser based (flash based, to be specific. Sorry to disappoint all my iPad toting readers) and doesn’t require any serious computing muscle on the player’s end. I’ve been playing it for the last hour or so, and it’s an odd piece of work. On the surface the game follows some basic rules of pattern matching casual games you might be familiar with like Bejeweled. Yet the experience of playing the game feels far more complex than that, and I don’t necessarily mean that in a bad way. Also, there’s a real benefit to playing this game on your spare time, other than gaining the l33t skills to pwn the n00bs with.

You see, Phylo is ‘a human computing framework for comparative genomics.’ Basically it gives you real multiple sequence alignment problems represented by 4 color blocks scattered on a grid. And of course, budding bio-enthusiasts like us know what’s up when a science programs give us 4 of anything- they represent nucleotide sequences. As you match same colored blocks with each other, you contribute some of your brain power to finding aligned sequences between different genes. If you misalign the blocks you lose a point, and if you create gaps between the blocks (which represent mutation) you lose lots of points. You can gain points by aligning same color blocks on vertical row and you need to gain certain amount of points to pass a level or get another gene to align with your existing sequence. This is a very abstract process of optimization that is usually done with complex computer algorithms and lots of processing power, which would be prohibitively expensive when brute-forced. The authors of the program hope to use the human-computer interaction on a large scale to come up with optimized heuristic pattern.

December 10th was the big day. NYC will never be the same. Let me elaborate: after two years of blood, sweat, and labor (only a few tears), we finally announced the birth of Genspace to the world on December 10th. The preparation leading to the big day way typical of the ragtag crew of Genspace: chaotic, intense, lasting way past most people’s bedtime, but mysteriously it worked out in the end.

Everyone showed up: art students, scientists, writers, and long lost faces from two years ago. Turns out two tables filled to the brim with food, wine and beer weren’t quite enough to accommodate the bio-curious (not to confuse our counterpart in SF crowd in the city. It’s almost funny how we worried that no one would turn up.

The entire laboratory was strewn with Christmas lights. A light box illuminated an algae bioreactor in testing at the space. Screens were set up showing videos of microscopic organisms, and on our desktop in the study a live feed of the strawberry tissue  streamed from $12 USB microscope in the lab. Even our neighbor Chris pulled out all the stops, demonstrating his  ‘animal sense’ contraption for people to try out.

We still have ways to go, however. We need to reach out to the population of the city and show them that science is within reach. We need to work ever harder to break the walls surrounding learning and practice of science, and we need to create ever more ingenious, useful, and beautiful things.

The Genspace grand opening isn’t about the past two years, it’s about the future from here on out. Let’s bring back the romance between the sciences and the public.  I am proud to be a founding member of the first community biotech laboratory in NYC.

Who knows, maybe we really will end up changing the world for the better.

I’m an official team member of the 2010 NYU iGEM team! I’ve learned a ton of biology from Russ, and worked on some cool stuff like visualizing and simulating the Immunoyeast system using Processing language. I’m also working on having a touch-screen installation for the Jamboree, so don’t forget to check it out if you plan on being there.

Genspace is up and running, and it is totally awesome. We collaborated with the BioBus at the World Maker Faire and won the Maker Editor’s Award, which is apparently a kind-of-big deal. I did about 40 DNA extraction, purification, PCR and restriction digest myself, teaching people about basic lab processes and a bit of theory behind genotyping. There were lots of screaming children and spitting involved, but it was totally worth it. The target of the exercise was TASR38 coding SNP, and I should have a detailed post of the whole process up in a few weeks.

There are tons of more stuff I should be writing about, and maybe I’ll find enough time to do that when the iGEM is over (although I’m already thinking about how awesome 2011 iGEM can be).

Back to the main post: I’ve been reading stuff written by Alan Kay again. I think it’s safe to say that he’s one of my all-time heroes by now. There’s a cool book about him and his work called Points of View available for free on the net. It’s not directly relevant to biology or physics, but if you’re interested in education, information abstraction and history it will be a fascinating read.

It’s not that I’m actively seeking out stuff about him. I just seem to run into them whenever I do research for my own projects, whether it be methods for abstracting complex sciences for public consumption or coming up with useful programming tools for beginner’s bioinformatics curriculum.

I was reading up a bit more on structure of Ruby and its use in bioinformatics. I eventually ran into the legendary Ruby hacker _why and his Shoes and Hackety Hack toolkits, which mysteriously led me to another one of Alan Kay’s letters, written in 1998 after OOPSLA. The piece itself isn’t directly relevant to biology. He just talks about how most people don’t really understand OOP in computer sciences and how it’s not really about objects but dynamic messages passed between objects. Here’s an excerpt from the letter I found interesting.

“The key in making great and growable systems is much more to design how its modules communicate rather than what their internal properties and behaviors should be.”

Alan Kay had biology background before he went into computer science and he explicitly stated that his most well-known achievement, OOP model and Smalltalk systems are inspired by biological processes… Which is one of the reasons why I tried to use Squeak Smalltalk system for earlier iteration of my synthetic biology curriculum for high school children (something I’m still working on and need a ton of help with). Considering that earlier versions of synthetic biology in form of BioBrick system is based on core engineering principles I can’t help but to think about possibility of re-applying Alan Kay’s OOP model back to biological systems.

BioBricks based synthetic biology strongly resembles ‘object’-oriented OOP paradigm, where people build parts with unique internal characteristics and then link them together into a whole system. Entire system is focused on functionality of the individual parts with almost no care taken to characterize and document how different parts interact with each other. It should be interesting to imagine a different type of synthetic biology where the biologist considers how different segments of DNA (or perhaps the system should be built on top of larger scale composite parts) modules communicate and work with each other, and how to coerce them into forming larger systems. Systems built on top of message passing rather than minute details of the molecular system.

Sigh, the more I learn about things the more I have to study.

EDIT:(Oct/31)

Now you might be wondering why anyone would ever want to worry about implementing true OOP like paradigm or message based system building in biological systems. The answer is simple. All these programming paradigms were created to handle complexity. When we consider that existing paradigm of synthetic biology borrows heavily from that created for engineering and programming computers (one of the prominent figures of synthetic biology, for example, is Tom Knight, of the original MIT lisp hacker fame), ability to handle complexity within engineered framework becomes a fundamentally important issue.

One of the main difference between silicon based computation and that within in-vivo environment is scalability. Conventional programming languages are not very dynamic, and are terrible at scaling up compared to biological systems. If we are to bring any sort of computational/engineering approach to biology we need to address the issue of scalability that works in orders of magnitude difference from initial state. Biological systems do not go through processor bottleneck to transition from one state to another, and they have billions of processes operating in parallel. Engineering and programming approached as we know them will not be very useful for long without efforts to address these issues.

Jaron Lanier, one of the pioneers of opensource movement and virtual reality, thinks the opensource movement had been a total failure. He does point out the opensource movement and the web culture are two different things and agrees the latter had been a phenomenal success in demonstrating the capacity of the unknown, average individuals out there to create beautiful, useful, and interesting things.

I don’t agree with everything he said, but I think he has some important points we should pay attention to.

1.Opensource movement is boring. Seriously, sitting down and writing Wikipedia entries (of often questionable accuracy), worrying about how to format texts? Sure, it’s something you and I might do in our spare time, but we are geeks. Opensource is about serving all of humanity, but as it stands opensource just serves the narrow interests of a very small portion of the population: Geeks and nerds. As long as grandma and primary schools kids next door can’t use opensource products/projects/frameworks simply because it’s fun, the whole culture is just another outlet for elitism and fascism most hackers are supposed to hate so much. Ever said something on the lines of ‘I hate being the tech support for the whole family’? That means the people who wrote those programs and services suck, not the users.

2.Major opensource products are built upon nostalgia of the ‘better times’, the golden age of the hackerdom during the 60′s~80′s. Linux, gcc the vast majority of the main opensource projects are built upon, vim vs. emacs war, and etc etc. Linux distros had been making some good strides in this department but we still need to face facts. To anyone who didn’t string together shell scripts when he/she was in high school, major opensource projects and the tools they are based upon look downright archaic. It isn’t because they have bad user interface design (they do). It’s because they really are old and deprecated. I am continuously amazed by how many people tell fresh young minds entering hackerdom to go learn C. Kindergartners don’t start learning English language by starting with Latin. Why is the whole darn culture based on a fast-but-bad programming language designed before many of us were born? Let’s be honest here, most people who recommend C to beginners started with BASIC. When a whole culture based on ideals of innovation and sharing begins to look outdated and conservative next to hulking multi-billion/trillion-dollar corporate entities, they are in trouble.

3.This is a repeat of above statement, but it bears some reiteration. There isn’t enough innovation in the opensource community. Again, large corporate entities that takes three days to ship an empty box innovates a whole lot more than most of the opensource communities out there. Sure, there had been some interesting developments that’s making the world a better place, like Ruby and Python. The same Ruby and Python people praise for finally getting around to implementing great ideas of programming languages like Smalltalk and Lisp. Smalltalk and Lisp was invented back when the idea of a cheap personal computer was the stuff of science fiction. Linux is playing catch up in terms of features and architecture with commercial operating systems and in critical applications UNIX is king (guess how old it is).  Meanwhile Microsoft is making strides with .NET framework and Google/Apple is on the cusp of next era of personal computing. Based on real world progress, opensource community as a whole lack clear vision of what the future should be.

4.There is an inherent elitism within a lot of the opensource communities. Personally I have no issue with elitism on personal level. It’s when such attitude permeates within entire communities that they begin to do real harm. Common sense dictates that any software targeted at Jane Doe should be easy enough for J.D. to use. Not so in a lot of opensource communities. If Jane Doe has hard time using an obscure text editor with more commands than the usual operating system it’s her fault for being so lazy and/or dumb. If a kid who can barely type can’t learn C and work with pointers the kid must be stupid. If it’s too difficult for artists to use computer systems to create beautiful things without pre-packaged software it’s because artsy types aren’t supposed to be good at computers. These problems are being addressed by a new wave of hackers and hacker-minded people but they are still tragically present in many of the present communities, even when they don’t specifically come out and say those things.

There are other interesting traits about opensource and opensource oriented communities Jaron Lanier pointed out as well, like how most of them are structured to shout down any voice of dissent based on fear of isolation, and how there is a culture of complacency among its leading members, but those things apply to almost any large group of people, so I felt no need to single out and discuss them.

I’m an optimist. I think there are movements within the opensource community that are trying to address this problem. I think the prevalence of web platforms, popularity of light weight scripting languages, and web/user interface designs are all in some form a reaction to the perceived stagnation of opensource community. People are increasingly becoming aware of what a stupid idea it is to teach C in middle schools, and how even stupider it is to begin computer education in a middle school instead of much, much earlier. I might go out on a limb and say that some people are beginning to realize that programming as an activity is not difficult at all, and that it is the teachers who don’t know what they are doing, not the students.

Yet I am still worried about the culture of opensource. Opensource as in framework of idea, not of computing. How can we apply the ideas of opensource and innovation to the fields outside computing, like CNC based personal manufacturing, scientific research and DIYbio when it’s running into such problems on what should be the culture’s home ground? Are those open-manufacturers/scientists/biohobbyists/etc about to run into unforeseen trouble inherent in existing idea of opensource itself? Are we already in trouble?

edit: maybe I should say that the woe of current opensource community (as a whole. There are many brilliant people and groups out there, can’t stress that enough) is that they don’t hack as much as smaller groups?

Edit: Aug 28
Some people wrote me some valid (“you don’t seem to understand opensource in the post”), and some vitriolic (“what’s wrong with being a nerd?!” but with lots of swearing in it), rebuttals to this post. I refrained from replying to those responses individually and getting into arguments since I think this post is terrible myself (like how I used opensource and web2.0 interchangeably throughout some of the parts). I must stress that I’m a student of all things Free software and what I say or write here should never be taken as something it isn’t.

I personally like to consider myself as someone with geek tendencies. I love emacs, and I love the idea of emacs. I think GCC is a huge thing that changed the course of humanity as much as development of steam engine changed the face of humanity forever. And yet I think all of those tools are old, based on older ideas and inaccessible to anyone who doesn’t subscribe to the lifestyles of people like you and me, the people who wouldn’t mind staring at a screen for hours on end.

I’ve had a chance to talk to some ex-programmers turned artists at the ITP exhibition last year. There was a particularly interesting exhibit with a type of evolving display system. He did all of the graphic generation within the exhibition by hand, by putting together a library of hand-drawn images. It was rather obvious he could simply do some coding in the Processing language and get it done faster and more efficiently, so I asked him why he bothered with the manual labor… And he told me that he simply doesn’t like to program. I’m not sure how I can portray the eye-opening effect it had on me at the time. The artist was fine with studying algorithms and working them out on paper, using it to generate obviously computational results. He was a very logical guy with mathematical proficiency to spare, certainly more than what I can say about myself. It’s only that he just couldn’t stand the whirring of the computer fans, the monitors, the endless clacking of keyboards and always worrying about battery life of one device or another. And I get a feeling that he is not alone in this. Maybe there are some people who are allergic to certain type of things used universally in building computers. Maybe there are some kids who just can’t handle the physical environment that comes with using a computer as we know it due to some psychological trauma. Such cases aren’t unheard-of in education circles and there can be hundreds of thousands of reasons why someone would shy away from programming activities while possessing logical acuity and vision that would normally lead to the act of programming.
I subscribe to the Alan Kay notion of describing computer-use: every interaction with a computer is an act of programming, but programming activity isn’t exclusive to usage of computer devices. And that’s why I agree with his frequent statement that the computer revolution never really happened. Computer revolution was supposed to be the revolution of the mind-ware. It was supposed to be this awesome tool of abstraction that would elevate (for lack of a better term) all of humanity to a state of freedom through better understanding of subjects that were distant and foreign to them… It was supposed to make science easier, a goal that is near and dear to people like me interested in DIYbiology. Easier not as in being lazy but being accessible, like how calculus was once considered the pinnacle of human knowledge but is now being taught even in some of the worst educational curriculums in the world as something every human being should know regardless of their intellectual rigor.
The original post was how I tried to address the inconsistency between the ideals that I believe should be applied to opensource community and the reality of the tools deployed. It’s called open-source, purists call it Free-software. Despite some differences between the two they really are about openness and freedom, but as long as its users and contributors subscribe to a certain type of lifestyle. Is there any way to change that? Can Free software be so free as to be no longer confined to the silicon and copper frameworks and languages of C and (gasp) Fortran?

I know this is all sounds like a pie-in-the-sky talk right now but I feel it’s a goal worth pursuing for those in the opensource community.

This post is, like it says in the title, a rant post of what DIYBio ought to be and how I plan to do my part this year. It’s also written on my blackberry which I later copy-pasted into the wordpress… I just hope half a year of writing boring technical stuff didn’t burn out creative writing part of my brain. I’ll be using it a lot from now on.

Year 2009 was series of exciting experiences, with ISFF, DIYBio and iGEM jamboree. I’m trying to pan it out into this year without losing momentum, through activities like synthetic biology crash course for beginners, various internships and private research projects. Hopefully I’ll have more time to write about them in the coming months.

I’ve been thinking a lot on diybio, about what it’s supposed to be & what it needs, and I think I’ve arrived at some sort of conclusion.

DIYBio must inevitably find the way to bridge the gap between the enthusiastic members of the public and tools and devices that makes synthetic biology feasible. While there are many members out there who seem to work toward specific gadgets and other physical tools of biological experiment, I think we still need something more.

DIY or not, biology is a science. If we want to bring hard science to the public with aid of ever cheapening yet sophisticated lab equipments we need to look beyond the hardware.

I’ve written quite a few times about Alan Kay (on this blog and elsewhere), the pioneer of modern computer programming/interface paradigm and his relationship with synthetic biology… There are mountains of information on him and his works that are relevant to the discussion of models in biology and how they might be used to organize information, with emphasis on education as a sort of interface between data and human mind… All of which are beyond the scope of this particular post.

The important point is this. I believe true potential for diybio is to bridge the gap between the complexity of bleeding edge science with the innate human ability to learn and tinker. And the main tool in making it happen is idea, not low cost lab tools (the costs of the lab tools are coming down anyway. Why DIY every single appliance when you can buy a used one that works just as good, oftentimes even better?). While low cost lab implementations are important, the true future lies with the ability to abstract and package/rebuild complexity into something much more manageable.

Some people seem to have difficulty understanding what I’m trying to say from the few times I’ve tried to talk about… I’m talking about reviving and revising the notion of knowledge engineering, something that was supposed to be the corner stone of true computer revolution that never really took off (google and wikipedia are some remnants of the original idea).

Synthetic biology is a good example of what knowledge engineering coupled with physical science might be able to achieve. None of the specific pieces forming what we perceive as synthetic biology are new. They’ve been around for quite a while in one form or another following course of gradual improvement rather than truly new scientific advance.
Synthetic biology at heart is about how dedicated professionals can organize scattered pieces of knowledge into something that can potentially allow ambitious undergraduate students to undertake projects that would have been beyond their ability a decade ago. Never mind the actual success rate of their projects for now. They very fact that those students are able to plan for the future with much broader sphere of possibility is significant enough.
And why stop with undergraduates? Wouldn’t it be possible to have motivated high school students design something that at least works on paper? Wouldn’t it be possible to build a conceptual framework so that those kids can at least discuss possibilities of future projects on back of a napkin without resorting to sci fi?

If diybio is to do what it originally set out to do, we need to look beyond gadgets and tools. We need to think about ideas and how they come together… We need to make biology easier, not just cheaper. This is the mantra that will drive my DIYBio related activities this year.

I know I should be writing about some other things as well, like how the diybio nyc might be amazingly close to getting a real lab space, or how I’m prepping to stop by for this year’s iGEM jamboree. I also have the pictures from this year’s major diybio nyc event, where we set up a stall on the NYC green market and extracted dnas from the natural produces with common household material (with the passers-by of course). Each of those things would probably make for some lengthy and interesting reading, and the list goes on (my life’s actually kind of exciting right now). Yet whenever I find the time to write something down, nada. Nothing. My mind just shuts down and nothing I can commit to paper or the keyboard seems good enough.

Tonight though, aided by my weird bout with insomnia, I’ll just write something down I’ve been meaning to say for a long time.

I’ve been looking into the history of computing and computer languages recently. I’ve always had some level of interest in computers. Not just the spiffy brand-new muscle machines but in what most people would refer to as ‘retrocomputing’ (I once ended up practicing some AIDA because of that. Ugh), which is a story for another time. It’s not that I think old ways of computing were better than what we have now (protected memory FTW). It’s just that it’s much easier to trace the evolution of the concept of computing when you see beyond the immediate commercial products.

Synthetic biology is effectively a pursuit of engineering biological organisms. Biological organisms are based upon somewhat unified information storage and processing system that has quite a bit of parallels to mechanical computerized systems. I’ve been wondering whether it would be possible to predict the future development of synthetic biology by looking at how computer programming languages evolved (because they deal with information processing systems applied to physical counting medium). Maybe it’d be possible to predict some of the pitfalls that are inherent in developing complex programmable information processing system that will apply to the synthetic biology in the future. Maybe we can bring a conceptual framework to the synthetic biology that would have taken decades if left to mature naturally to within mere years.

While I was rummaging through the texts in both real life and the web (with many of the promising links on the web leading to dead-ends and 404s) I ran into a programming paradigm and environment I was only superficially familiar with before. Smalltalk and Squeak, both the brainchild of the computing pioneer Alan Kay.

Here’s an excerpt from Alan Kay’s biography I found on the net (I can’t find the website right now. I swear I’ll edit it in later, when my brain’s actually working!)

“Alan Kay postulated that the ideal computer would function like a living organism; each “cell” would behave in accord with others to accomplish an end goal but would also be able to function autonomously. Cells could also regroup themselves in order to attack another problem or handle another function.”

This is the basic philosophy behind smalltalk/squeak and object oriented computer programming paradigm. It is no coincidence that Alan Kay’s vision of the ideal computer language and computing environment would take to a biological allegory, since he came from molecular biology background.

While I’m reading through the history of different computing paradigms for the purpose of figuring out how it might be applied to synthetic biology, there’s something else I found awesome and perhaps a little heartwarming. Alan Kay throughout his life as a computing pioneer held onto the belief that the ideal computing platform won’t be a platform capable of crunching numbers the fastest. It will be a platform that can be integrated into the educational function of the user through ease of manipulation and control. Ideal computing platform should be hackable because it makes logical sense to do so.

Can we say the same of synthetic biology? Perhaps not. The direct comparison of a complex biological system to computerized circuits can only take us so far. Yet I can’t shake the nagging feeling that synthetic biology might be looking at some very unique opportunities for change precisely because it is different from regular electronic systems, with documents of the early days of computer and programming already here for our perusal.

A good, elegant system that allows programmable extension must be at the same time easy to learn, since one thing must inevitably lead to the other. And there are classes of systems that both run and learn better compared to other systems. This might become something of an issue of how synthetic biology parts/devices/systems are put together in the future as the capacity of the synthetic biologists to handle complex systems increase.

I think it might be able to pursue this idea further. As it stands this is nothing more than an interesting parallel in concept without substantial scientific reasoning.

Which is why I should get myself to learn smalltalk/squeak sometime in the future. Maybe I should knock on the hackerspaces in the city, see if anyone’s willing to mentor me.