Public Intelligence Blog

Jean Lievens

Bioengineers Build Open Source Language for Programming Cells

• By Daniela Hernandez
• WIRED Magazine
• 04.19.13

Drew Endy wants to build a programming language for the body.

Endy is the co-director of the International Open Facility Advancing Biotechnology — BIOFAB, for short — where he’s part of a team that’s developing a language that will use genetic data to actually program biological cells. That may seem like the stuff of science fiction, but the project is already underway, and the team intends to open source the language, so that other scientists can use it and modify it and perfect it.

Click on Image to Enlarge

The effort is part of a sweeping movement to grab hold of our genetic data and directly improve the way our bodies behave — a process known as bioengineering. With the Supreme Court exploring whether genes can be patented, the bioengineering world is at crossroads, but scientists like Endy continue to push this technology forward.

Genes contain information that defines the way our cells function, and some parts of the genome express themselves in much the same way across different types of cells and organisms. This would allow Endy and his team to build a language scientists could use to carefully engineer gene expression – what they call “the layer between the genome and all the dynamic processes of life.”

According to Ziv Bar-Joseph, a computational biologist at Carnegie Mellon University, gene expression isn’t that different from the way computing systems talk to each other. You see the same behavior in system after system. “That’s also very common in computing,” he says. Indeed, since the ’60s, computers have been built to operate much like cells and other biologically systems. They’re self-contained operations with standard ways of trading information with each other.

The BIOFAB project is still in the early stages. Endy and the team are creating the most basic of building blocks — the “grammar” for the language. Their latest achievement, recently reported in the journal Science, has been to create a way of controlling and amplifying the signals sent from the genome to the cell. Endy compares this process to an old fashioned telegraph.

Read full article.

Patrick Meier

Zooniverse — The Answer to Big (Crisis) Data?

Both humanitarian and development organizations are completely unprepared to deal with the rise of “Big Crisis Data” & “Big Development Data.” But many still hope that Big Data is but an illusion. Not so, as I’ve already blogged here, here and here. This explains why I’m on a quest to tame the Big Data Beast. Enter Zooniverse. I’ve been a huge fan of Zooniverse for as long as I can remember, and certainly long before I first mentioned them in this post from two years ago. Zooniverse is a citizen science platform that evolved from GalaxyZoo in 2007. Today, Zooniverse “hosts more than a dozen projects which allow volunteers to participate in scientific research” (1). So, why do I have a major “techie crush” on Zooniverse?

Oh let me count the ways. Zooniverse interfaces are absolutely gorgeous, making them a real pleasure to spend time with; they really understand user-centered design and motivations. The fact that Zooniverse is conversent in multiple disciplines is incredibly attractive. Indeed, the platform has been used to produce rich scientific data across multiple fields such as astronomy, ecology and climate science. Furthermore, this citizen science beauty has a user-base of some 800,000 registered volunteers—with an average of 500 to 1,000 new volunteers joining every day! To place this into context, the Standby Volunteer Task Force (SBTF), a digital humanitarian group has about 1,000 volunteers in total. The open source Zooniverse platform also scales like there’s no tomorrow, enabling hundreds of thousands to participate on a single deployment at any given time. In short, the software supporting these pioneering citizen science projects is well tested and rapidly customizable.

. . . . . . . . . .

One of the most attractive features of many microtasking platforms such as Zooniverse is quality control. Think of slot machines. The only way to win big is by having three matching figures such as the three yellow bells in the picture above (righthand side). Hit the jackpot and the coins will flow. Get two out three matching figures (lefthand side), and some slot machines may toss you a few coins for your efforts. Microtasking uses the same approach. Only if three participants tag the same picture of a galaxy as being a spiral galaxy does that data point count. (Of course, you could decide to change the requirement from 3 volunteers to 5 or even 20 volunteers). This important feature allows micro-tasking initiatives to ensure a high standard of data quality, which may explain why many Zooniverse projects have resulted in major scientific break-throughs over the years.

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Stuart Umpleby

Here is a fragment from a listserve that is related to reflexivity.  It explains how social science is different from physical science.  Assuming that an approach developed for physical systems can also be used for social systems will miss a key feature of social systems.

Very interesting paper on application of science to agriculture, in which the authors come up with this very interesting notion of ‘systemic science’:

“A systemic science is a science that influences its own subject area.”

This explicitly tackles the challenge thrown down by Michel Foucault concerning the human sciences, for which the problematic was that their object of study (say the human mind) was at the same time their subject (us humans studying that object of study).  The application to agricultural is very clear, succinct and makes very good sense of such a systemic science.  Don’t know the authors and haven’t come across any of their previous work. The paper is longish but very readable:

PDF 31 Pages: ‘Towards a systemic research methodology in agriculture: Rethinking the role of values in science’.

Hugo Fjelsted Alrøe and Erik Steen Kristensen

Further explanation of this notion of ‘systemic science’:

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Steve Wheeler
Click for BIo Page

01 Facing the future
At the end of each year many of us tend to focus on the future, wondering what it will bring. We wish each other a happy New Year, and hope that life will treat us kindly. We try to shape our own futures by making New Year resolutions, many of which fall by the wayside after a week or two. Much of our future is not ours to shape. But still we persist in trying to predict the future.  Many of our predictions about the future are based on speculation or wishful thinking.

02 Is technology making us smarter?
When discussing the future, especially the future of technology, there are some writers who almost always seem to be quoted. Near the top of the list is the futurologist Ray Kurzweil, who has much to say about our technological future, and also about the growth in human intelligence. His views are quite optimistic, especially around computers and the nature of knowledge.

03 The future of intelligence
In my previous blog post I examined the debate about whether we are becoming more intelligent or less intelligent as a result of our prolonged and habituated uses of technology.

04 The future of classrooms
What will be the future of school classrooms? It is unlikely that we will see the demise of the classroom in the next decade. Those who study the future of education often suggest that the demise of traditional classrooms is not only inevitable, but imminent.

Parts 04-09 Below the Line.

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