Researchers make DNA data storage a reality: Every film and TV program ever created -- in a teacup

Jan. 23, 2013 — Researchers at the EMBL-European Bioinformatics Institute (EMBL-EBI) have created a way to store data in the form of DNA – a material that lasts for tens of thousands of years. The new method, published January 23 in the journal Nature, makes it possible to store at least 100 million hours of high-definition video in about a cup of DNA.

There is a lot of digital information in the world – about three zettabytes’ worth (that’s 3000 billion billion bytes) – and the constant influx of new digital content poses a real challenge for archivists. Hard disks are expensive and require a constant supply of electricity, while even the best ‘no-power’ archiving materials such as magnetic tape degrade within a decade. This is a growing problem in the life sciences, where massive volumes of data – including DNA sequences – make up the fabric of the scientific record.

"We already know that DNA is a robust way to store information because we can extract it from bones of woolly mammoths, which date back tens of thousands of years, and make sense of it,” explains Nick Goldman of EMBL-EBI. “It’s also incredibly small, dense and does not need any power for storage, so shipping and keeping it is easy.”

Reading DNA is fairly straightforward, but writing it has until now been a major hurdle to making DNA storage a reality. There are two challenges: first, using current methods it is only possible to manufacture DNA in short strings. Secondly, both writing and reading DNA are prone to errors, particularly when the same DNA letter is repeated. Nick Goldman and co-author Ewan Birney, Associate Director of EMBL-EBI, set out to create a code that overcomes both problems.

“We knew we needed to make a code using only short strings of DNA, and to do it in such a way that creating a run of the same letter would be impossible. So we figured, let’s break up the code into lots of overlapping fragments going in both directions, with indexing information showing where each fragment belongs in the overall code, and make a coding scheme that doesn't allow repeats. That way, you would have to have the same error on four different fragments for it to fail – and that would be very rare," says Ewan Birney.

The new method requires synthesising DNA from the encoded information: enter Agilent Technologies, Inc, a California-based company that volunteered its services. Ewan Birney and Nick Goldman sent them encoded versions of: an .mp3 of Martin Luther King’s speech, “I Have a Dream”; a .jpg photo of EMBL-EBI; a .pdf of Watson and Crick’s seminal paper, “Molecular structure of nucleic acids”; a .txt file of all of Shakespeare's sonnets; and a file that describes the encoding.

“We downloaded the files from the Web and used them to synthesise hundreds of thousands of pieces of DNA – the result looks like a tiny piece of dust,” explains Emily Leproust of Agilent. Agilent mailed the sample to EMBL-EBI, where the researchers were able to sequence the DNA and decode the files without errors.

“We’ve created a code that's error tolerant using a molecular form we know will last in the right conditions for 10 000 years, or possibly longer,” says Nick Goldman. “As long as someone knows what the code is, you will be able to read it back if you have a machine that can read DNA.”

Although there are many practical aspects to solve, the inherent density and longevity of DNA makes it an attractive storage medium. The next step for the researchers is to perfect the coding scheme and explore practical aspects, paving the way for a commercially viable DNA storage model.

Share this story on Facebook, Twitter, and Google:

Other social bookmarking and sharing tools:

Story Source:

The above story is reprinted from materials provided by European Molecular Biology Laboratory (EMBL).

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Journal Reference:

Nick Goldman, Paul Bertone, Siyuan Chen, Christophe Dessimoz, Emily M. LeProust, Botond Sipos, Ewan Birney. Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature, 2013; DOI: 10.1038/nature11875

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Education: Get with the computer program

ScienceDaily (Oct. 5, 2012) — From email to Twitter, blogs to word processors, computer programs provide countless communications opportunities. While social applications have dominated the development of the participatory web for users and programmers alike, this era of Web 2.0 is applicable to more than just networking opportunities: it impacts education.

The integration of increasingly sophisticated information and communication tools (ICTs) is sweeping university classrooms. Understanding how learners and instructors perceive the effectiveness of these tools in the classroom is critical to the success or failure of their integration higher education settings. A new study led by Concordia University shows that when it comes to pedagogy, students prefer an engaging lecture rather than a targeted tweet.

Twelve universities across Quebec recently signed up to be a part of the first cross-provincial study of perceptions of ICT integration and course effectiveness on higher learning. This represented the first pan-provincial study to assess how professors are making the leap from lectures to LinkedIn -- and whether students are up for the change to the traditional educational model.

At the forefront of this study was Concordia's own Vivek Venkatesh. As associate dean of academic programs and development within the School of Graduate Studies, he has a particular interest in how education is evolving within post-secondary institutions. To conduct the study, Venkatesh partnered with Magda Fusaro from UQAM's Department of Management and Technology. Together, they conducted a pilot project at UQAM before rolling the project out to universities across the province.

"We hit the ground running and received an overwhelmingly positive response with 15,020 students and 2,640 instructors responding to our electronic questionnaires in February and March of 2011," recalls Venkatesh. The 120-item surveys gauged course structure preferences, perceptions of the usefulness of teaching methods, and the level of technology knowledge of both students and teachers.

The surprising results showed that students were more appreciative of the literally "old school" approach of lectures and were less enthusiastic than teachers about using ICTs in classes. Instructors were more fluent with the use of emails than with social media, while the opposite was true for students.

"Our analysis showed that teachers think that their students feel more positive about their classroom learning experience if there are more interactive, discussion-oriented activities. In reality, engaging and stimulating lectures, regardless of how technologies are used, are what really predict students' appreciation of a given university course," explains Fusaro.

The researchers hope these results will have a broad impact, especially in terms of curriculum design and professional development. For Venkatesh, "this project represents a true success story of collaboration across Québec universities that could definitely have an effect outside the province." Indeed, the large number of participants involved means this research is applicable to populations of learners across North America and Europe with similar educational and information technology infrastructures. An electronic revolution could soon sweep post-secondary classrooms around the world, thanks to this brand new research from Quebec.

Share this story on Facebook, Twitter, and Google:

Other social bookmarking and sharing tools:

Story Source:

The above story is reprinted from materials provided by Concordia University.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Journal Reference:

Kamran Shaikh, Vivek Venkatesh, Tieja Thomas, Kathryn Urbaniak, Timothy Gallant, David I., Amna Zuberi. Technological Transparency in the Age of Web 2.0: A Case Study of Interactions in Internet-Based Forums. InTech, 2012 DOI: 10.5772/29082

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Computer program can identify rough sketches

ScienceDaily (Sep. 13, 2012) — First they took over chess. Then Jeopardy. Soon, computers could make the ideal partner in a game of Draw Something (or its forebear, Pictionary).

Researchers from Brown University and the Technical University of Berlin have developed a computer program that can recognize sketches as they're drawn in real time. It's the first computer application that enables "semantic understanding" of abstract sketches, the researchers say. The advance could clear the way for vastly improved sketch-based interface and search applications.

The research behind the program was presented last month at SIGGRAPH, the world's premier computer graphics conference. The paper is now available online (http://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/), together with a video, a library of sample sketches, and other materials.

Computers are already pretty good at matching sketches to objects as long as the sketches are accurate representations. For example, applications have been developed that can match police sketches to actual faces in mug shots. But iconic or abstract sketches -- the kind that most people are able to easily produce -- are another matter entirely.

For example, if you were asked to sketch a rabbit, you might draw a cartoony-looking thing with big ears, buckteeth, and a cotton tail. Another person probably wouldn't have much trouble recognizing your funny bunny as a rabbit -- despite the fact that it doesn't look all that much like a real rabbit.

"It might be that we only recognize it as a rabbit because we all grew up that way," said James Hays, assistant professor of computer science at Brown, who developed the new program with Mathias Eitz and Marc Alexa from the Technical University in Berlin. "Whoever got the ball rolling on caricaturing rabbits like that, that's just how we all draw them now."

Getting a computer to understand what we've come to understand through years of cartoons and coloring books is a monumentally difficult task. The key to making this new program work, Hays says, is a large database of sketches that could be used to teach a computer how humans sketch objects. "This is really the first time anybody has examined a large database of actual sketches," Hays said.

To put the database together, the researchers first came up with a list of everyday objects that people might be inclined to sketch. "We looked at an existing computer vision dataset called LabelMe, which has a lot of annotated photographs," Hays said. "We looked at the label frequency and we got the most popular objects in photographs. Then we added other things of interest that we thought might occur in sketches, like rainbows for example."

They ended up with a set of 250 object categories. Then the researchers used Mechanical Turk, a crowdsourcing marketplace run by Amazon, to hire people to sketch objects from each category -- 20,000 sketches in all. Those data were then fed into existing recognition and machine learning algorithms to teach the program which sketches belong to which categories. From there, the team developed an interface where users input new sketches, and the computer tries to identify them in real time, as quickly as the user draws them.

As it is now, the program successfully identifies sketches with around 56-percent accuracy, as long as the object is included in one of the 250 categories. That's not bad, considering that when the researchers asked actual humans to identify sketches in the database, they managed about 73-percent accuracy. "The gap between human and computational performance is not so big, not as big certainly as it is in other computer vision problems," Hays said.

The program isn't ready to rule Pictionary just yet, mainly because of its limited 250-category vocabulary. But expanding it to include more categories is a possibility, Hays says. One way to do that might be to turn the program into a game and collect the data that players input. The team has already made a free iPhone/iPad app that could be gamified.

"The game could ask you to sketch something and if another person is able to successfully recognize it, then we can say that must have been a decent enough sketch," he said. "You could collect all sorts of training data that way."

And that kind of crowdsourced data has been key to the project so far.

"It was the data gathering that had been holding this back, not the digital representation or the machine learning; those have been around for a decade," Hays said. "There's just no way to learn to recognize say, sketches of lions, based on just a clever algorithm. The algorithm really needs to see close to 100 instances of how people draw lions, and then it becomes possible to tell lions from potted plants."

Ultimately a program like this one could end up being much more than just fun and games. It could be used to develop better sketch-based interface and search applications. Despite the ubiquity of touch screens, sketch-based search still isn't widely used, but that's probably because it simply hasn't worked very well, Hays says.

A better sketch-based interface might improve computer accessibility. "Directly searching for some visual shape is probably easier in some domains," Hays said. "It avoids all language issues; that's certainly one thing."

Share this story on Facebook, Twitter, and Google:

Other social bookmarking and sharing tools:

Story Source:

The above story is reprinted from materials provided by Brown University.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here