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Undergraduates:
If you are interested in working with
the Synthetic Biology team during the 2009-2010 academic year, you are
invited to attend a meeting in
BSLC 214 at 6:00pm on October 6th, 2008. If you cannot
attend this meeting,
please submit a brief resume and one-page cover letter to synbio@uchicago.edu.
Include
relevant statements about your research experience, area(s) of
specialty (molecular biology, genetics, computer science, chemistry,
mathematics, etc), and skills (programming languages, exceptional
memory/study habits, etc).
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Welcome
to the website of Gene Hackers, the Synthetic Biology research team at
the University of Chicago. Please feel free to navigate the site using
the links above, and contact
us with any questions or comments you may have.
Research Overview
The definition of synthetic
biology has been generally accepted as the
engineering of biology:
the synthesis of complex, biologically based (or inspired) systems,
which display functions that do not exist in nature. This engineering
perspective may be applied at all levels of the hierarchy of biological
structures—from individual molecules to whole cells, tissues and
organisms. In essence, synthetic biology will enable the design of
'biological systems' in a rational and systematic way (Synthetic
Biology: Applying Engineering to Biology: Report of a NEST High Level
Expert Group).
Our efforts to develop a
biological programming language is the literal
intepretation of the genome as the language of biology. Long-term aims
of our group include collaborating with other labs, utilizing
linguistic (and other) techniques to describe this language in formal
mathemtical terms.
Short-term goals
include the analysis of mussel adhesion proteins (MAPs), and
organization of systems based upon sequence data and the methods of
synthetic biology, in order to gain proof-of-principle data. We work
with
Mefp-5, Mefp-3, and recombinant fp-151; our model organisms are
E. coli and C. crescentus.
What
is Synthetic Biology?
The
basic ideas underlying synthetic biology are really quite simple:
1.
Automated (DNA) Construction
2. Standards of Abstraction
Abstraction
is the process of generalization by reducing the
information content of a concept or an observable phenomenon, typically
in order to retain only information which is relevant for a particular
purpose. It is a mechanism and practice to reduce and
factor out details so that one may focus on a few concepts at a time.
For example, abstracting “a well-worn, bouncy basketball” to simply “a
ball” retains only the information on the attributes and behavior of a
general ball. Similarly, abstracting an emotional state to “happiness”
or “sadness” reduces the amount of information conveyed about the
emotional state. However, these abstractions allow us to
hide complexity, and utilize a greater amount of parts in a simpler
design.
In synthetic biology, genetic code is abstracted into chunks, known
primarily as biological "parts." These parts allow us to build
increasingly complex systems; putting several parts together creates a
"device," which is regulated by start codons, stop codons, restriction
sites, and similar coding regions known as "features." Please visit MIT's
Standard Registry of Parts for more detailed information, and
tutorials on how to make your own biological part!
In
short, we are interested in designing and synthesizing artificial
biological systems in a systematic, rational manner. This is about developing
a biological programming language. We want to move from
an ad-hoc research approach to a scalable engineering framework. We
hope to accomplish this through a comprehensive and collaborative study
of genetics, systems biology, computer science, and many rounds of
trial-and-error.
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“Biology
is a technology for processing information, materials, and energy. As a
technology platform, biological systems provide access to artifacts and
processes across a range of scales (e.g., the ribosome is a
programmable nanoassembler, a bamboo shoot can grow 12” a day). Biology
also forms the basis for human welfare (e.g., modest amounts of memory
and logic, implemented as genetically encoded systems, would directly
impact biological research and medicine). However, our ability to
deploy biology as a technology and to interact internationally with the
living world is now limited; the charge to our study was to
begin to specify enabling technology that, if developed, would provide
a general foundation for the engineering of biology and make routine
the creation of synthetic biological systems that behave as predicted.”
--Drew Endy, 2003
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