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Open Source DNA?
Eugene
Thacker
[eugene.thacker@lcc.gatech.edu]
School of Literature, Communication,
& Culture
Georgia Institute of Technology
(Note: parts
of text also to appear in Biotech Hobbyist Magazine)
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 "bioinformatics." 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 "a technology-driven
quest."
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 "life"?
Download, Tweak, Upload
The
title of this paper is more of a question than any sort of statement.
What would it mean to have "open source DNA"? How might we define
a group of heterogeneous activities under this name? What is open source
DNA?
In
the same way that the open source movements have raised issues concerning
the production, development, distribution, and use of software systems,
open source DNA could do something similar for the combined fields of
molecular biology and computer science (including other areas, such as
A-life, molecular modeling, telemedicine, complexity, network computing,
and so forth).
Is
there a need for open source DNA? From one perspective, DNA is already
open source: the publicly-funded human genome project makes its findings
available to the public through its GenBank database and website, just
as other academic and government-funded projects do for proteins, SNPs,
RNA, and other biological components. In addition, a number of software
applications are available as freeware or shareware, along with the increasing
number of research applications which function online (again, mostly from
academic institutions).
But
as we know, this is not the whole picture Many datasets are privatized
(such as those held by Celera, DoubleTwist, or Human Genome Sciences)
and have exorbitantly high subscription rates (mostly intended for pharmaceutical
corporations). In addition, a great deal of the computer tools which undergirds
biotech research (hardware, software, and wetware) come at a great cost,
with little or no low-tech or low-cost alternatives. Even when such tools
are available, their learning curve is high enough that usually some background
in either computer science, computer programming, database systems, statistics,
or molecular biology is required. For individuals or groups working outside
of specialized fields (artists, educators, activists, cultural theorists)
,and for those within such fields with only partial knowledge of biotech
(scientists and engineers in other fields), the barriers to becoming active
in biotech can be overwhelming.
Therefore
the necessity for open source DNA is both political and technical. It
is political because there is much critical and creative work to be done
in relation to biotech’s general approach to the body, medicine, and perspectives
on biological "life" itself (see Critical Art Ensemble’s book
Flesh Machine for more). But it is also technical, because in order that
any effective intervention in biotech can take place, the basic knowledges,
skill sets, and tools of biotech must first be made available to individuals
and groups outside of its specified disciplines, institutions, or corporations.
A Discipline or an Industry?
The
interesting thing about bioinformatics is that, on the one hand, it is
a new discipline, a hybrid of knowledges and techniques from computer
science, as well as molecular biology. But on the other hand, bioinformatics
has risen hand-in-hand with new companies, proprietary software, and a
range of products and services.
Broadly
speaking, bioinformatics includes several activities:
First
there are the so-called "pick-and-shovel" companies. As the
name indicates, these are companies that make the tools needed for biotech
research, where research and product development are one in the same.
Such tools can be software applications (such as Incyte Genomics’ "Lifeseq"
software suite), they can be hardware (such as Affymetrix’s "GeneChip"
microarray system), they can be database and networking tools (such as
those offered by DoubleTwist), or they can be a combination of IT solutions
for biotech research (such as those offered by Lion Bioscience).
Secondly,
there are organizations which deal in handling biological data. The most
familiar examples are the human genome teams, the public-funded groups
(such as the National Center for Biotechnology Information, or NCBI) and
Celera Genomics, a private genomics company. Both institutions house their
own data on the human genome, the main difference being that while the
NCBI offers its databases to the public, Celera charges for access on
a corporate-level subscription basis.
Finally,
there are research groups (many which exist at universities) whose primary
interest is in developing novel ways of applying computer science to molecular
biology research problems (Bioinformatics.org and Open Bioinformatics
are examples). Research can range from the very practical (e.g., how to
apply techniques in computer error detection towards genetic scanning)
to the more radical (e.g., using AI or a-life to develop "intelligent"
bioinformatics software apps).
Certainly,
these are not definite boundaries, as nearly all biotech research requires
computational tools of some kind. In addition, the past few years has
seen a growing interest in computer industry and biotech industry mergers
because of bioinformatics (e.g., Sun and DoubleTwist, IBM, Compaq and
Celera, Motorola). Therefore, it is important to note that although bioinformatics
may be an "emerging" discipline, in many ways it is already
mature in its relationships with institutions, corporations, and academic
disciplines.
This
is worth noting because it means that any "alternative" approaches
in bioinformatics and uses of biological data, will have to confront issues
such as access to information, access to tools, development of skill sets,
distribution of knowledge, and the challenges of trans-disciplinary work.
The main question which is put forth is: How does an individual or group
acquire the knowledge, skills, resources, and tools needed to work in
a non-orthodox manner in biotech?
Not
surprisingly, artists have been among the first to explore such questions.
But the results are often less than satisfactory, even when art-science
collaboration is involved; too often the resulting works operate only
at the symbolic or representational level. However, such art-science projects
have been instrumental in raising critical and political issues with regard
to biotech, suggesting that a new type of serious research can co-exist
alongside a critical and political consciousness.
We
might begin, then, by elaborating a series of theoretical questions which
bioinformatics raises. From there we can consider possible fields of research
in biotech to look into, and then begin asking practical questions.
Soft Machines: Theoretical Questions
The
human genome projects seem to suggest to us that flesh and data are equivalent:
DNA can be extracted from an individual’s body, then encoded into digital
format (using flouresence tagging), then sequenced and uploaded into an
online database. That data can then be used in diagnostics, genetically-tailored
drug design, gene therapy, or in regenerative medicine therapies. But
is DNA really equivalent to binary code? Elsewhere, I have referred to
this back-and-forth exchange between digital and analog DNA as "biomedia":
the "translatability" of the genome between digital and analog.
In the techniques of genomics, it is taken for granted that the wet DNA
in a test tube is somehow "essentially" the same as the dry
DNA spelled out on a computer database. But the larger implications of
this technical assumptions are dangerous --it suggests that the true essence
of the genome is not the material "stuff" out of which it is
made, but rather some source code which exists irrespective of material
instantiation (see Haraway, Hayles, and Kay for more). It seems that one
of the questions which bioinformatics asks, is how much we can really
claim to be uploading biological materials, and how much we are just cataloguing
the body. Could a critical bioinformatics emerge from this, in which the
situated, embodied character of the biological body is always taken into
account, while never being totally divided from the informatic domain?
If so, what are some of the challenges it would face?
In
the same way that open source has contributed to a DIY computer culture
and various types of hacker ethics, could the design of innovative bioinformatics
software apps, combined with public access to the genome, spawn a DIY
biotech culture? Could an increase demand on public access medical data,
combined with advances in telemedicine, generate a new type of homeopathic
health care? At the furthest reaches of the extreme, how might this "open
source DNA" movement affect areas such as media art, education, body
performance, regenerative medicine, body art, and wet computing?
Although
there is a great diversity in biotech research, much of it has continued
to focus on genes and the genome as their primary targets (as company
patent portfolios illustrate). This single-minded approach has been countered
recently by alternative approaches borrowing from systems theory and complexity.
How might we think about the intersection between computer science and
molecular biology be rethought as a hybrid discipline? What novel knowledges
are produced in their intersection? What might the role of computer technology
be, if it is to be more than a mere tool for bioscience research? How
might each discipline not just aid, but actually transform the other?
While
questions of ethics are always given at least a conciliatory nod in any
discussion of biotech, ethics needs to be rethought with respect to biotech.
One starting point may be the ethical debates generated by the discourses
on open source, patent protection, and "hacktivism." Would an
open source DNA movement confront the same ethical and political challenges
that the open source software movements have? In this sense, how would
a politically-motivated, open source DNA be different from forms of hacktivism?
How would it be different from the controversial activities labeled "bioterrorism"?
How might a genuine bioethical protocol be established, such that biotech
resources are not used irresponsibly?
Soft Machines: Practical
Considerations
As
a way of fostering some workshop-type thinking on this topic, we can form
a beginning list of concerns for open source DNA:
- What kinds of resources are currently available to the public,
and in what kinds of formats? For instance, what types of data does
the NCBI’s human genome dataset make available? Is its format compatible
with XML-based software apps such as those made by Rosetta InPharmatics?
How much of this data is accessible online? How much of it depends on
specialized software? What types of publicly available networks can
be formed around such concerns?
- What kinds of tools and applications are available for biotech
research? What kinds of research do they make possible? How many of
these apps -- if any -- are freeware or shareware? Are these applications
open source? If not, what programming knowledge sets are they based
on? Many bioinformatics apps are based on XML -- could this open the
way for an XML-based open biosoftware initiative?
- How might open source DNA labs be set up in a manner that is compliant
with safety, technical requirements, networking, and efficient access
to resources? How can the computer lab and the molecular biology lab
be integrated in innovative ways? How might further computer science
-- molecular biology collaborations be fostered in this area? How might
various institutional bodies aid in the formation of such labs (grants,
foundations, universities)?
- What are some immediate practical and political consequences of
open source DNA? At the policy level, at the health care level, at the
research level, at the economic/corporate level, and at the industry
level? How can cultural and political-activist projects be effectively
realized in these fields?
Blood Music
As
a cultural theorist of science and technology, this intersection of computer
science and molecular biology has many significant impacts outside of
the sciences. For one, biotech fields like bioinformatics are practically
demonstrating the ways in which boundary between the body and technology
are being transformed, and, in some cases, effaced altogether. No longer
is the body the privileged domain of "nature," just as our technologies
are more than inert objects we simply control and use. It appears that
biotech research is delving deeper into the carbon-silicon barrier, and
finding not a barrier at all, but rather a permeable membrane that is
constantly changing its shape.
This
philosophical transformation has direct impacts in the political concerns
over germline gene modification, DNA screening and privacy (bio-cryptography?),
biopiracy and biocolonialism (population and ethic genomes), and pharmacogenomics
(genetically-tailored drugs). Ethical concerns over "tampering with
nature," biodiversity conservation, economies of biological materials,
and other concerns all arise in part from the way in which the relationship
between bodies and technologies is viewed.
Likewise,
science fiction has, for a long time, imagined the extreme possibilities
- both positive and negative - which biotech brings with it. Examples
of such extreme biotech (BioX?) include: full-body regeneration (X-Men),
replicant engineering (Blade Runner), next-gen horror movie efx ("bodies
that splatter"), biotech telerobotics ("The Girl Who Was Plugged
In"), biomolecular morphing (The Thing), bio-fashion (Schismatrix),
and biomolecular consciousness (Blood Music).
However
fanciful such visions may seem, they point to the need for alternative
approaches for thinking about the biomolecular body. In actual science
research, approaches such as systems biology, autopoiesis, self-organization,
biopathways, epigenetics, and CAS (complex adaptive systems) are all pointing
to different ways of thinking about biological life beyond the centrality
of DNA or the genome.
Bioinformatics
is the key to rethinking computer science & molecular biology across
their traditional disciplinary divisions. While there are pragmatic examples
of the ways in which computational approaches are advancing biotech research
(such as the HGP), bioinformatics places flesh and data in such an intimate
proximity that it challenges us to think of technology beyond the tool,
just as it challenges us to think of biology as much more complex than
a "master molecule" residing in nature.
References
Bear,
Greg. Blood Music. New York: Ace, 1983.
Benton,
D. "Bioinformatics: Principles and Potential of a New Multidisciplinary
Tool." Trends In Biotechnology 14(8):261-72 (August 1996).
Bioinform
http://www.bioinform.com
Bioinformatics.org
http://www.bioinformatics.org
Critical
Art Ensemble. Flesh Machine: Cyborgs, Designer Babies, and New Eugenic
Consciousness. Brooklyn: Autonomedia, 1998.
Gershon,
Diane. "Bioinformatics in a Post-Genomics Age." Nature 389 (27
September 1997): 417-18.
Haraway,
Donna. Modest_Witness@Second_Millennium.FemaleMan©_Meets_OncoMouse™: Feminism
and Technoscience. New York: Routledge, 1997.
Hayles,
N. Katherine. How We Became Posthuman: Virtual Bodies in Cybernetics,
Literature, and Informatics. Chicago: U of Chicago P, 1999.
Howard,
Ken. "The Bioinformatics Gold Rush." Scientific American (July
2000): 58-63.
Kay,
Lily. Who Wrote the Book of Life? A History of the Genetic Code. Stanford:
Stanford, 2000.
Open
Bioinformatics http://www.open-bio.org
Palsson,
Bernhard. "The challenges of in silico biology." Nature Biotechnology
18 (November 2000): 1147-50.
Persidis,
Aris. "Bioinformatics." Nature Biotechnology 17 (August 1999):
828-830.
The
Scientist. Special Issue: The State of Bioinformatics. The Scientist 14.3
(27 November 2000).
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