Eugene Thacker on Wed, 3 Oct 2001 19:38:57 +0200 (CEST)


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[Nettime-bold] Open Source DNA?


[This text appears as part of the Wizards of OS 2 conference:
http://wizards-of-os.org]

Open Source DNA?

Eugene Thacker 

 
Opening the Biomolecular Black Box

What follows here is a series of observations, comments, and reflections on
the current intersections between computer science and molecular biology. In
conjunction with issues pertaining to open source initiatives, this aim of
this paper is to raise similar questions in the domain of biotechnology.

All of us have witnessed the media-hype generated by such biotech issues as
the human genome, human cloning, and debates over the use of embryonic stem
cells. But what often goes unmentioned is that the real generator of radical
change in fields like biotech is not genome mapping, cloning, or genetic
engineering ­ it is ³bioinformatics.² Put simply, bioinformatics is a
growing discipline which straddles computer science and molecular biology
(here at Georgia Tech, where I teach, the first bioinformatics degree
program was established in 1999). Currently, bioinformatics mostly means the
use of computer technology to aid in the study of life (that is, new tools
for molecular genetics and biomedicine). Already, over the past decade or
so, numerous companies have formed which specialize in the application of
computer science to solve problems in biotech research. The recent race to
map the human genome is one such example: both the public and private teams
made use of automated genome sequencing computers built by Perkin-Elmer.
Without the aid of specialized software and hardware, research on the human
genome would not have made the progress it claims to have made thus far.
Last year, the investment firm Oscar Gruss & Co. released a study of the
field, suggesting that bioinformatics may generate some $2 billion over the
next five years. As the New York Times put it, the human genome has, for
better or worse, been ³a technology-driven quest.²

But is that all that bioinformatics is? In other words, what other kinds of
developments can emerge out of this intersection between computer science
and molecular biology, between computer code and genetic code, between data
and flesh? Could it be that approaches from computing (network theories,
systems theories, parallel processing, a-life) might have something to teach
us about the complexity of the organism? Could such approaches even
transform the way in which molecular genetics and biotech has traditionally
thought of the organism, the body, and biological ³life²?

[text continued at:
http://www.mikro.org/Events/OS/text/Eugene-Thacker_OSDNA.htm]




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Eugene Thacker, Assistant Prof
e: eugene.thacker@lcc.gatech.edu
School of Literature, Communication & Culture
Georgia Institute of Technology
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