SynBioFromLeukipposInstitute

By Caroline Arbanas

"Our bodies contain far more microbial genes than human genes. And a new study suggests that just as human DNA varies from person to person, so too does the massive collection of microbial DNA in the intestine.

The research is the first to catalog the genetic variation of microbes that live in the gut, where they extract nutrients from food, synthesize vitamins, protect against infections, and produce compounds that naturally reduce inflammation. The widespread genetic diversity uncovered by the scientists can help them understand how our microbial genes work together with our human genes to keep us healthy or, in some cases, to cause disease."

A new genomics research center sits at the nexus of medicine, science, engineering and the humanities. The goal is nothing short of improving human well-being.

by

U. TORONTO

"It looks like a smiley face tattoo, but a new easy-to-apply sensor can detect medical problems and help athletes fine-tune training routines.“We wanted a design that could conceal the electrodes,” says Vinci Hung, a PhD candidate in physical and environmental sciences at the University of Toronto, who helped create the new sensor. “We also wanted to showcase the variety of designs that can be accomplished with this fabrication technique.”
The tattoo, which is an ion-selective electrode (ISE), is made using standard screen printing technique and commercially available transfer tattoo paper—the same kind of paper that usually carries tattoos of Spiderman or Disney princesses.
In the case of the sensor, the “eyes” function as the working and reference electrodes, and the “ears” are contacts for a measurement device to connect to.
Hung contributed to the work while in the lab of Joseph Wang, a professor at the University of California, San Diego. The sensor she helped make can detect changes in the skin’s pH levels in response to metabolic stress from exertion...."

http://bit.ly/R1Gfa5

Brain without a body

"A computationally advanced, million-neuron model of the brain successfully demonstrates perception, cognition, and behavior. "

A Large-Scale Model of the Functioning Brain

by
Chris Eliasmith, Terrence C. Stewart, Xuan Choo, Trevor Bekolay, Travis DeWolf, Charlie Tang, Daniel Rasmussen

"A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called “Spaun”) that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks."
http://bit.ly/TwWRBX

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Building the Human Brain

by
Christian K. Machens

"The human brain is exceedingly complex and studying it encompasses gathering information across a range of levels, from molecular processes to behavior. The sheer breadth of this undertaking has perhaps led to an increased specialization of brain research and a concomitant fragmentation of our knowledge. A potential solution is to integrate all of this knowledge into a coherent simulation of the brain (1). However, simply “building” a brain from the bottom up by replicating its parts, connections, and organization fails to capture its essential function—complex behavior (2). Instead, just as engineers can only construct cars and computers because they know how they work, we will only be able to construct a brain if we know how it works—that is, if we understand the computations that are carried out in individual brain areas, and how these computations are implemented on the level of neural networks. On page 1202 of this issue, Eliasmith et al. (3) make headway toward this benchmark by presenting just such a large-scale computational model of the human brain that can simulate a variety of complex behaviors."

http://bit.ly/U6CFGa

Biological Pathways and the Semantic Web...

WikiPathways (www.wikipathways.org) is a community-driven pathway resource [1-3]. It is inspired by Wikipedia and aims at capturing knowledge about biological pathways in such a way that it can be used for data analysis. For the Innovative Medicine Initiative project Open PHACTS [4], we expose the contents of WikiPathways in semantic web format. We are taking a multi-pronged approach, selecting different ontologies to capture diverse aspects of semantics. As an established pathway ontology, BioPAX [5] forms the bulk of the semantics for the actual pathway content, but we also use other specialized ontologies to capture the semantics of curators, authors, and other WikiPathways-specific meta data.

"Computer scientists prove that networks of cells can compute as efficiently as networks of computers linked via the internet

Distributed computing is all the rage these days. The idea is to break down computational tasks into convenient chunks and distribute them across a network to a number of computers. The benefits are clear, such as easy, on-demand access to huge computing resources.

The conventional way to think about these systems is as independent Turing machines connected by a network that allows them to exchange large messages. This so-called ‘message passing model’ certainly applies to much of the distributed computing that takes place on the internet; projects such as the SETI@home and the Einstein @home programs.

But there is a growing awareness that many networks are much more limited, both in the size of the messages they can transmit and receive and also in the processing capacity at each node.

A biological cell, for example, can transmit and receive only limited amounts of information and can perform only rudimentary processing tasks. It’s easy to imagine that a network of cells can perform only very simple distributed computing tasks. On the other hand, perhaps they can make up for their individual deficiencies by working as a group and so are just as capable as other networks.

So an important question is how these limitations influence the classes of distributed computing tasks that groups of cells can perform.

Today we have an answer thanks to the work of Yuval Emek, Jasmin Smula and Roger Wattenhofer at the Swiss Federal Institute of Technology in Zurich. “We believe that there is a need for a network model, where nodes are by design below the computation and communication capabilities of Turing machines,” they say.

These guys have modelled the computing behaviour of a network of these sub-Turing machines, which they call finite state machines. They show that far from being critically handicapped, a network of finite state machines is capable of solving many of the standard problems in conventional distributed computing, such as the 3-colouring of undirected trees .

What’s more, these networks can do the job just as efficiently–in a time that is poly-logarithmic with the number of cells.

That could turn out to have far reaching consequences. It may be a stretch to imagine a network of cells joining the SETI@home project. But it provides a framework in which to study how networks of cells might solve other common problems in biological systems such as forward planning, trajectory calculations and so on.

The new model can also be applied in more prosaic ways, such as predicting the performance of networks of sensors which are strongly constricted by power limitations.

Emek and co ask the question: “do tiny bio/nano nodes “compute” and/or “communicate” essentially [in] the same [way] as a computer?”

The answer, it would seem, is yes, which means it is an exciting time to be a distributed computing specialist working in biology."
http://bit.ly/11sDwIA

Fifty-nine years after James Watson and Francis Crick deduced the double-helix structure of DNA, a scientist has captured the first direct photograph of the twisted ladder that props up life.

The Biological Computer Laboratory (BCL) was a research institute of the Department of Electrical Engineering at the University of Illinois at Urbana-Champaign. It was founded on 1 January 1958 by the then Professor of Electrical Engineering Heinz Foerster. The focus of research at the BCL was systems theory and specifically the area of self-organizing systems, bionics, and bio-inspired computing; that is, analyzing, formalizing, and implementing biological process using computers.

Heinz Foerster is one of the most important scientists of the 20 century. He was a visionary and his work has a fundamental impact on contemporary bio medical science. He is a central figure in the development of systems theory, the fundament of systems biology and synthetic biology.

*Ref*.:
http://bit.ly/m9kpNY

BCL homepage http://bcl.ece.illinois.edu

Heinz Foerster homepage http://www.univie.ac.at/constructivism/HvF.htm
Heinz von Foerster and the Bio-Computing Movements of the 1960s

http://www.stim.illinois.edu/unfinishedrev/11_asaro.pdf

http://www.amazon.com/Unfinished-Revolution-Biological-Laboratory-1958-1976/dp/3901941126

Notes on an epistemology for living things http://ada.evergreen.edu/~arunc/texts/cybernetics/heinz/epistemology/bcl9.3.pd

Biological computing from Heinz von Foerster to the present: a tool for understanding intelligence? http://atomiumculture.eu/content/biological-computing-heinz-von-foerster-present-tool-understanding-intelligence

http://en.wikipedia.org/wiki/Cybernetics

"Researchers at the Wyss Institute for Biologically Inspired Engineering at Harvard University have created more than 100 three-dimensional (3D) nanostructures using DNA building blocks that function like Lego® bricks — a major advance from the two-dimensional (2D) structures the same team built a few months ago."

http://bit.ly/11sbNa3

Curiosity drives humanity. When confronted with a new phenomenon, we are compelled to search for understanding. We can then control the science with new technologies, making life easier.

by

Kevin D Litcofsky, Raffi B Afeyan, Russell J Krom, Ahmad S Khalil & James J Collins

"We present a methodology for the design, construction and modification of synthetic gene networks. This method emphasizes post-assembly modification of constructs based on network behavior, thus facilitating iterative design strategies and rapid tuning and repurposing of gene networks. The ease of post-construction modification afforded by this approach and the ever-increasing repository of components within the framework will help accelerate the development of functional genetic circuits for synthetic biology."
http://bit.ly/Twa4vp

A free PDF from the Collins lab can be found here:
http://www.bu.edu/abl/files/naturemethods_litcofsky.pdf