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Mostrando entradas con la etiqueta Language. Mostrar todas las entradas

martes, 5 de abril de 2016

A programming language for living cells

MIT biological engineers have devised a programming language that can be used to give new functions to E. coli bacteria.
Image: Janet Iwasa
New language lets researchers design novel biological circuits.
MIT biological engineers have created a programming language that allows them to rapidly design complex, DNA-encoded circuits that give new functions to living cells.

Using this language, anyone can write a program for the function they want, such as detecting and responding to certain environmental conditions. They can then generate a DNA sequence that will achieve it.

It is literally a programming language for bacteria,” says Christopher Voigt, an MIT professor of biological engineering. “You use a text-based language, just like you’re programming a computer. Then you take that text and you compile it and it turns it into a DNA sequence that you put into the cell, and the circuit runs inside the cell.

Voigt and colleagues at Boston University and the National Institute of Standards and Technology have used this language, which they describe in the April 1 issue of Science, to build circuits that can detect up to three inputs and respond in different ways. Future applications for this kind of programming include designing bacterial cells that can produce a cancer drug when they detect a tumor, or creating yeast cells that can halt their own fermentation process if too many toxic byproducts build up.

The researchers plan to make the user design interface available on the Web.

No experience needed
Over the past 15 years, biologists and engineers have designed many genetic parts, such as sensors, memory switches, and biological clocks, that can be combined to modify existing cell functions and add new ones.

However, designing each circuit is a laborious process that requires great expertise and often a lot of trial and error. “You have to have this really intimate knowledge of how those pieces are going to work and how they’re going to come together,” Voigt says.

Users of the new programming language, however, need no special knowledge of genetic engineering.

You could be completely naive as to how any of it works. That’s what’s really different about this,” Voigt says. “You could be a student in high school and go onto the Web-based server and type out the program you want, and it spits back the DNA sequence.

The language is based on Verilog, which is commonly used to program computer chips. To create a version of the language that would work for cells, the researchers designed computing elements such as logic gates and sensors that can be encoded in a bacterial cell’s DNA. The sensors can detect different compounds, such as oxygen or glucose, as well as light, temperature, acidity, and other environmental conditions. Users can also add their own sensors. “It’s very customizable,” Voigt says.

The biggest challenge, he says, was designing the 14 logic gates used in the circuits so that they wouldn’t interfere with each other once placed in the complex environment of a living cell.

In the current version of the programming language, these genetic parts are optimized for E. coli, but the researchers are working on expanding the language for other strains of bacteria, including Bacteroides, commonly found in the human gut, and Pseudomonas, which often lives in plant roots, as well as the yeast Saccharomyces cerevisiae. This would allow users to write a single program and then compile it for different organisms to get the right DNA sequence for each one.

Biological circuits
Using this language, the researchers programmed 60 circuits with different functions, and 45 of them worked correctly the first time they were tested. Many of the circuits were designed to measure one or more environmental conditions, such as oxygen level or glucose concentration, and respond accordingly. Another circuit was designed to rank three different inputs and then respond based on the priority of each one.

One of the new circuits is the largest biological circuit ever built, containing seven logic gates and about 12,000 base pairs of DNA.

Another advantage of this technique is its speed. Until now, “it would take years to build these types of circuits. Now you just hit the button and immediately get a DNA sequence to test,” Voigt says.

His team plans to work on several different applications using this approach: bacteria that can be swallowed to aid in digestion of lactose; bacteria that can live on plant roots and produce insecticide if they sense the plant is under attack; and yeast that can be engineered to shut off when they are producing too many toxic byproducts in a fermentation reactor.

The lead author of the Science paper is MIT graduate student Alec Nielsen. Other authors are former MIT postdoc Bryan Der, MIT postdoc Jonghyeon Shin, Boston University graduate student Prashant Vaidyanathan, Boston University associate professor Douglas Densmore, and National Institute of Standards and Technology researchers Vanya Paralanov, Elizabeth Strychalski, and David Ross.

ORIGINAL: MIT
Anne Trafton | MIT News Office 
March 31, 2016

lunes, 16 de noviembre de 2015

Network of artificial neurons learns to use language

Neurons. Shutterstock
A network of artificial neurons has learned how to use language.

Researchers from the universities of Sassari and Plymouth found that their cognitive model, made up of two million interconnected artificial neurons, was able to learn to use language without any prior knowledge.

The model is called the Artificial Neural Network with Adaptive Behaviour Exploited for Language Learning -- or the slightly catchier Annabell for short. Researchers hope Annabell will help shed light on the cognitive processes that underpin language development. 

Annabell has no pre-coded knowledge of language, and learned through communication with a human interlocutor. 

"The system is capable of learning to communicate through natural language starting from tabula rasa, without any prior knowledge of the structure of phrases, meaning of words [or] role of the different classes of words, and only by interacting with a human through a text-based interface," researchers said.

"It is also able to learn nouns, verbs, adjectives, pronouns and other word classes and to use them in expressive language.

Annabell was able to learn due to two functional mechanisms -- synaptic plasticity and neural gating, both of which are present in the human brain.

  • Synaptic plasticity: refers to the brain's ability to increase efficiency when the connection between two neurons are activated simultaneously, and is linked to learning and memory.
  • Neural gating mechanisms: play an important role in the cortex by modulating neurons, behaving like 'switches' that turn particular behaviours on and off. When turned on, they transmit a signal; when off, they block the signal. Annabell is able to learn using these mechanisms, as the flow of information inputted into the system is controlled in different areas
"The results show that, compared to previous cognitive neural models of language, the Annabell model is able to develop a broad range of functionalities, starting from a tabula rasa condition," researchers said in their conclusion

"The current version of the system sets the scene for subsequent experiments on the fluidity of the brain and its robustness. It could lead to the extension of the model for handling the developmental stages in the grounding and acquisition of language."

ORIGINAL: Wired - UK
13 NOVEMBER 15 

jueves, 15 de octubre de 2015

Why we need to talk about science


Image: Scientist prepares solutions for tests. REUTERS/Suzanne Plunkett
In this presidential election season, one thing is certain: candidates will rarely – if ever – be asked what they would do to keep the United States at the forefront of science and innovation.

That’s a shame.

The public dialogue about science is perhaps the most vital and most fraught national conversation not taking place in the US, and the ramifications are profound.

Ultimately, the way we address science and innovation will determine what our children learn in school, what college graduates bring to the larger world, how public lands and natural resources are cared for and whether people receive adequate health care. And the list goes on.

As the president of one of our country’s leading research university systems, I believe it is now incumbent on the academic community to ensure that the work and voices of researchers are front and center in the public square.

Calling all scientists
When the voices of scientists are not heard in the dialogue, there is a price to pay.

As Stanford University’s Charlotte DeCroes Jacobs made clear in her recent excellent biography, Jonas Salk, A Life, the fanfare brought Salk the everlasting disdain of some of his scientific colleagues, but it proved to serve the greater public good.

It is important that scientists be seen as regular people asking and answering important questions.

Our country needs more scientists who are willing and able to step out in the public arena and to weigh in, clearly and strongly – such as atmospheric physicist Veerabhadran Ramanathan of UC San Diego, who discovered the greenhouse effect of halocarbons in 1975.

Dr Ramanathan is a member of the Pontifical Academy of Sciences that influenced Pope Francis to speak out on global climate change.

We need more scientists who can explain what they are doing in language that is compelling and understandable to the public – for example, astrophysicist and Hayden Planetarium Director Neil deGrasse Tyson, whose use of television and social media earned him the US National Academy of Sciences Public Welfare medal this year for “exciting the public about the wonders of science.”

Those of us in the academic community who are not scientists should also be prepared to support public engagement by scientists, and to incorporate scientific knowledge into our public communications.

I know from conversations I have had with other higher education leaders that I am not the only one who believes this is important.

Understanding mysteries of research
Too many people in this country – and that includes some among our elected leadership – still do not understand how science works or why robust, long-range investments in research vitally matter.

The truth is in the numbers. In the 1960s, the United States devoted nearly 17% of discretionary spending to research and development, reaping decades of economic growth from this sustained investment. By 2008, the figure had fallen into the single digits. This occurs at a time when the private sector has cut back on its research investment and other nations have made significant gains in their own research capabilities.

China, for example, is projected to outspend the United States in research within the next decade. East Asia as a whole already does.

At the University of California, we pride ourselves not only on the quality of our research, but also on its contribution to improving aspects of the world we live in.

It is UC’s research, for example, that has made California among the most robust agricultural regions of the world.

To hasten the development of science from the lab bench to the market place, UC is investing our own money in our own good ideas.

This past summer, we launched the first primeUC competition, which will award US$300,000 to winning start-ups in the health sciences. And last year, our Board of Regents approved the creation of a new $250 million fund, designed to provide seed money for direct investment into student and faculty inventions.

It also is possible to have some fun in demonstrating the broad, societal significance of research.

Introducing Grad Slam
Last May, I had the opportunity to emcee the first-ever University of California system-wide Grad Slam.

The Grad Slam asked UC graduate students to take their years of academic toil and research, and present their work to an audience in just three minutes, free of jargon or technical lingo.

Think of these presentations as TED talks on steroids or the ultimate in elevator speeches. Each of our 10 campuses held a local competition, and the finals took place at our system-wide headquarters in Oakland. Several of those finalists are featured on The Conversation’s website.

While it was a fun event, the purpose was very serious.

Good, sound science depends on hypotheses, experiments and reasoned methodologies. It requires a willingness to ask new questions and try new approaches. It requires one to take risks and experience failures.

But good, sound science also requires 

  • clear explanation
  • succinct presentation and 
  • contextual understanding

Telling the story is half the battle, and Grad Slam is perfect practice.

‘An eternal guide to truth’
On the flip side, the US needs more politicians who understand science and recognize it as more than window dressing for photo ops at school science fairs or opportunities to come before the cameras in white lab coats.

Scientists, of course, should not lose their focus on conducting research in the lab or the field, sharing knowledge with their peers, and supervising the postdocs and graduate students who will serve as the scientists of tomorrow.

In today’s world, however, society will benefit from scientists who also are able to raise the profile of science in the public dialogue.

In the rim of the dome of the National Academy of Sciences, there is an inscription that reads:
To science, pilot of industry, conqueror of disease, multiplier of the harvest, explorer of the universe, revealer of nature’s laws, eternal guide to truth.

This is a fine, noble and trenchant statement of what science is all about. It is a statement that must be made to come alive in the nation’s public conscience, and in the public and political narrative.

For more than 200 years, science and research have been the source of our country’s greatest strengths, and the promise of its bright future.

Now more than ever, it is incumbent on scientists to put their knowledge on the table, and for others in the academic community to support them in that endeavor.

This article is published in collaboration with The Conversation. Publication does not imply endorsement of views by the World Economic Forum.

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Author: Janet Napolitano is the 20th president of the University of California.

Oct 14 2015

miércoles, 22 de mayo de 2013

Synthetic Biology Open Language Visual (SBOL Visual), version 1.0.0 RFC

ORIGINAL: MIT / SBOL

Synthetic Biology Open Language Visual (SBOL Visual), version 1.0.0
Download
Author: Quinn, Jacqueline; Beal, Jacob; Bhatia, Swapnil; Cai, Patrick; Chen, Joanna; Clancy, Kevin; Hillson, Nathan; Galdzicki, Michal; Maheshwari, Akshay; P, Umesh; Pocock, Matthew; Rodriguez, Cesar; Stan, Guy-Bart; Endy, Drew
Citable URI: http://hdl.handle.net/1721.1/78249
Date Issued: 2013-03-31
Abstract:
In this BioBricks Foundation Request for Comments (BBF RFC), we specify the Synthetic Biology Open Language Visual standard (SBOL Visual) to enable consistent, human-readable depiction of genetic designs.
URI: http://hdl.handle.net/1721.1/78249
Series/Report no.: BBF RFC;93
Keywords: exchange, data, biobrick

SBOL Visual Examples


ORIGINAL: SBOL
Synthetic Biology Open Language (SBOL) is an open-source standard for in silico representation of genetic designs. SBOL is designed to:
  • Allow synthetic biologists and genetic engineers to electronically exchange designs
  • Send and receive genetic designs to and from biofabrication centers
  • Facilitate storage of genetic designs in repositories
  • Embed genetic designs in publications
SBOL is built around the idea of a core that is used to unambiguously specify the design of a DNA molecule. Around the core are extensions that are used to increase the kind and amount of information transmitted by the language. There are six extensions under development. For example, one extension includes data and information on the performance of DNA components.

The adoption of SBOL offers many benefits, including: 
  1. enabling the use of multiple tools without rewriting designs for each tool, 
  2. enabling designs to be shared and published in a form other researchers can use even in a different software environment, and 
  3. ensuring the survival of design (and the intellectual effort put into them) beyond the lifetime of the software or the reseachers that were used to create them.
Adopting SBOL
SBOL comprises of an object model and a serialization of SBOL to a file. The file is a machine-readable format form representing designs in synthetic biology. SBOL is neutral with respect to programming languages and software encoding. By supporting SBOL for reading and writing synthetic biology designs, different software tools can directly communicate and store the same representation of these designs. This removes an impediment to sharing engineered systems and permits other researchers and commercial enterprises to start with an unambiguous representation of the design.

The supported serialization is SBOL:Core:rdf:xml. This SBOL serialization is a supported import and/or export format in many synthetic biology tools. GenBank files may be serialized in SBOL and SBOL serializations may be converted to Genbank files using JBEI's j5 SBOL XML <--> GenBank Conversion Utility.

If you are a software developer for synthetic biology, you should grab one of the libSBOL libraries. Java library libSBOLj can import and export the SBOL core file format v1.1. There is also a C/C++ based library, libSBOLc, being written by Jeffrey Johnson that can export and import the files in the same SBOL format. Therefore, Java developers can use the native Java library, and others can use the C/C++ library, either natively or by using bindings for other languages.

The examples page illustrates a variety of DNA designs specified using the core.
SBOL Developers
SBOL's development started in 2008 with a small grant from MS. Since then it has grown to include a wide consortium of individuals, public institutions, and commercial enterprises both in the US and Europe.

The SBOL Developers Group meets roughly twice a year to discuss progress of the standard. Work on libSBOL and SBOL's icrosoftvarious extensions is ongoing. To join the developers group, contact the Editors at 
sbol-editors@googlegroups.org.