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February 19 2014

Four short links: 19 February 2014

  1. 1746 Slippy Map of London — very nice use of Google Maps to recontextualise historic maps. (via USvTh3m)
  2. TPP Comic — the comic explaining TPP that you’ve been waiting for. (via BoingBoing)
  3. Synthetic Biology Investor’s Lament — some hypotheses about why synbio is so slow to fire.
  4. vizcities — open source 3D (OpenGL) city and data visualisation platform, using open data.

February 06 2014

Academic biology and its discontents

When we started BioCoder, we assumed that we were addressing the DIYbio community: interested amateur hobbyists and experimenters without much formal background in biology, who were learning and working in independent hackerspaces.

A couple of conversations have made me question that assumption — not that DIYbio exists; it’s clearly a healthy and growing movement, with new labs and hackerspaces starting in most major cities. But there’s another group mixed in with the amateurs, with a distinctly different set of capabilities and goals. DIYbio doesn’t mean exactly what we thought it did.

That group is what I broadly call “disaffected grad students and postdocs.” They’ve got training, loads of it. But they’ve spent the last few years working in a laboratory under a faculty member, furthering that faculty member’s agenda. They have their own ideas and their own research projects, but they can’t work on them within the context of academic biology. They’re funded by a grant, and the grant will only pay for certain things. And, as Anthony Di Franco points out in “Superseding Institutions in Science and Medicine” (in the current issue of BioCoder), grants are primarily given to people who already know what they’re going to find, and that is not how you get truly innovative and creative research.

So, grad students and postdocs are increasingly turning to the DIYbio scene to do work that makes a difference. Some are working within established labs like Genspace or BioCurious; others are building garage labs or kitchen labs of their own; and still others are working in more advanced biohacker facilities such as Berkeley BioLabs or Bio, Tech, & Beyond. These organizations offer mentoring, advice on fundraising, marketing, and other business issues. Their goal is to make it easier for professional biologists to get a startup off the ground. They aren’t all that different from other tech incubators, just with lab benches and centrifuges. QB3, the California Institute for Quantitative Biosciences, even offers a “Startup in a Box” kit for entrepreneurs in biology.

What’s important about the “disaffected postdoc” phenomenon is that it answers one of the biggest questions about the coming revolution in biotech. Sure, a student can make glowing E. coli. That’s the “hello world” of synthetic biology. Making a glowing plant is a lot harder, and still requires PhD-level expertise. That’s changing, as we understand what it means for synthetic biology to become an engineering discipline. We have a catalog of standard biological parts, we have tools for designing DNA, and we can outsource the actual DNA synthesis. It has gotten much easier to do innovative work, and we expect it to get even easier. But the bar to real innovation is still set very high, and it will be some time before we see many bioscience startups founded by enthusiastic amateurs.

Grad students and postdocs who are leaving academia have already gotten over that bar. They’re a critical missing piece to the puzzle: they have the knowledge and creativity necessary to drive biological innovation in the near term. And some of their innovation will be spent developing the tools that will open up biology to a much wider range of participants.

June 21 2012

Four short links: 21 June 2012

  1. Test, Learn, Adapt (PDF) -- UK Cabinet Office paper on randomised trials for public policy. Ben Goldacre cowrote.
  2. UK EscapeTheCity Raises GBP600k in Crowd Equity -- took just eight days, using the Crowdcube platform for equity-based crowd investment.
  3. DIY Bio SOPs -- CC-licensed set of standard operating procedures for a bio lab. These are the SOPs that I provided to the Irish EPA as part of my "Consent Conditions" for "Contained Use of Class 1 Genetically Modified Microorganisms". (via Alison Marigold)
  4. Shuffling Cards -- shuffle a deck of cards until it's randomised. That order of cards probably hasn't ever been seen before in the history of mankind.

June 14 2010

Four short links: 14 June 2010

  1. Learning from Libraries: the Literacy Challenge of Open Data (David Eaves) -- a powerful continuation of the theme from my Rethinking Open Data post. David observes that dumping data over the fence isn't enough, we must help citizens engage. We have a model for that help, in the form of libraries: We didn’t build libraries for an already literate citizenry. We built libraries to help citizens become literate. Today we build open data portals not because we have a data or public policy literate citizenry, we build them so that citizens may become literate in data, visualization, coding and public policy.
  2. OpenPCR on Kickstarter -- In 1983, Kary Mullis first developed PCR, for which he later received a Nobel Prize. But the tool is still expensive, even though the technology is almost 30 years old. If computing grew at the same pace, we would all still be paying $2,000+ for a 1 MHz Apple II computer. Innovation in biotech needs a kick start!
  3. Wingeing It -- profile of O'Reilly's wonderful Sara Winge by the ever fabulous Quinn Norton.
  4. PEGASUS -- petascale graph mining toolkit from CMU. See their most recent publication. (via univerself on Delicious)

November 10 2009

Four short links: 10 November 2009

  1. A children’s toy inspires a cheap, easy production method for high-tech diagnostic chips -- microfluidic chips (with tiny liquid-filled channels) can cost $100k and more. Michelle Khine used the Shrinky Dinks childrens' toy to make her own. "I thought if I could print out the [designs] at a certain resolution and then make them shrink, I could make channels the right size for micro­fluidics," she says. (via BoingBoing)
  2. Complete Genomics publishes in Science on low-cost sequencing of 3 human genomes (press release) -- The consumables cost for these three genomes sequenced on the proof-of-principle genomic DNA nanoarrays ranged from $8,005 for 87x coverage to $1,726 for 45x coverage for the samples described in this report. Drive that cost down! There's a gold rush in biological discovery at the moment as we pick the low-hanging fruit of gross correlations between genome and physiome, but the science to reveal the workings of cause and effect is still in its infancy. We're in the position of the 18th century natural philosophers who were playing with static electricity, oxygen, anaesthetics, and so on but who lacked today's deeper insights into physical and chemical structure that explain the effects they were able to obtain. More data at this stage means more low-hanging fruit can be plucked, but the real power comes when we understand "how" and not just "what". (via BoingBoing)
  3. Far From a Lab? Turn a Cellphone into a Microscope (NY Times) -- for some tests, you can use a camphone instead of a microscope. In one prototype, a slide holding a finger prick of blood can be inserted over the phone’s camera sensor. The sensor detects the slide’s contents and sends the information wirelessly to a hospital or regional health center. For instance, the phones can detect the asymmetric shape of diseased blood cells or other abnormal cells, or note an increase of white blood cells, a sign of infection, he said.
  4. Augmented reality helps Marine mechanics carry out repair work (MIT TR) -- A user wears a head-worn display, and the AR system provides assistance by showing 3-D arrows that point to a relevant component, text instructions, floating labels and warnings, and animated, 3-D models of the appropriate tools. An Android-powered G1 smart phone attached to the mechanic's wrist provides touchscreen controls for cueing up the next sequence of instructions. [...] The mechanics using the AR system located and started repair tasks 56 percent faster, on average, than when wearing the untracked headset, and 47 percent faster than when using just a stationary computer screen.

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