Contemporary developments within the sciences of genetic engineering and biotechnology have been instrumental in constellating a series of relationships that are bringing together research in molecular biology (genetics, biotech, immunology, endocrinology), developments in applied research and clinical technologies (genomic mapping, gene therapy, PCR, DNA chips), and a variety of legal, social, and ethical issues (biotech & corporatization, patenting issues, genetic screening & DNA fingerprinting). For example, in May of this year, Perkin-Elmer Corporation (a leading supplier of “life systems” technologies for research and analysis in the pharmaceutical, biotechnology, environmental, and agricultural industries), The Institute for Genomic Research (TIGR – a not-for-profit genetic analysis organization), and Dr. J. Craig Venter (a controversial genetic researcher and director of TIGR) announced that a new genomics company would be formed with the intent of completing the mapping of the human genome in less time and for less money than the government-supported Human Genome Project. The alliance between Perkin-Elmer, Venter, and TIGR (whose website icon consists of a tiger leaping from a double helix of DNA) not only constitutes an important shift from national or government-supported research to a commercial or corporate frame, but it also marks an important encircling of research and development, a technology industry (new sequencing-machines produced by Perkin-Elmer), and commerce.
The excerpted files which follow in this essay are intended to raise some of the theoretical and technical issues that have manifested themselves within the domains of genetics and biotechnology research. This is made especially evident by the move of many technoscientific practices onto the Internet and Web, from searchable genomic databases, to computer applications used for protein modeling, to software programs designed to simulate and/or predict biochemical processes. In this literal – or rather, materialized – instance of genetic/biochemical and computer-based/network-based information, what gets defined or is assumed to constitute such objects as “information,” “gene,” and “database” has direct relationships and consequences for what constitutes the body, the individual, and the property of the social subject.
From these issues, two main points are emphasized. First, these technoscientific practices and logics form discrete examples where the relationship between the body and language is reconfigured as a relationship of materiality and data/information. Secondly, this manifestation has been occurring in a socio-cultural site thoroughly enframed by the technological apparatus of computer and telecommunications-based developments, contributing to the increasingly intimate conjunction of molecular science research and technological development that constitutes contemporary technoscience.
A technoscientific laboratory, in which a culturally marked, naked human body stands supported in a volumetric scanning chamber. The resultant 3-D model of the body is viewable on a nearby computer monitor. The interface on the monitor centrally frames the 3-D rendering of the body, rotating it and tilting it, presenting it as a bright green wireframe model, or as a full-volume body with rendered tones approximating flesh. Below and to the left of the rotating model of the body are information input/output windows (scanning level, rendering in polygon units, motion-capture data). Biomonitoring readouts relate the physiological and biochemical homeostasis of the body. Also, there is a scrolling readout of the individual’s genetic code and, within the same interface, a smaller inset-window relating the genetic code to this particular body’s physiological and biochemical properties.
Select the “segmentation” command: (1) The full, 3-D body-scan is partitioned horizontally and vertically into intersecting planes (sagittal, median, coronal, transverse), which outline various cavities of the body (ventral – comprised of thoracic, abdominal, pelvic cavities, and dorsal – comprised of cranial and spinal cavities). (2) Select any one of these sections (which become highlighted as the mouse-pointer passes over it) and zoom in. Select the “layer” command, which can represent this portion of the body as photo-quality flesh, as an assemblage of internal organs, or as a skeletal structure. View as an assemblage of internal organs: the text-prompt informs you that the body is comprised of a set of interworking “systems” (skeletal, nervous, muscular, reproductive, endocrine, circulatory, digestive, respiratory). The rapidly scrolling text reads: “In anatomical and physiological analysis, a system is an organization of varying numbers and kinds of organs so arranged that together they can perform complex functions for the body.” (3) Select any one of the illuminated organs in the body cavity section and zoom in. A rotating model of the selected organ comes into view, similarly presented as a wireframe model. The text prompt: “An organ is a complex organization of several different kinds of tissues so arranged that together they can perform a specific function related to the physiological system of which they are a part. For example, the stomach is composed of muscle, connective, epithelial, and nervous tissues. Muscle and connective tissues form its wall, epithelial and connective tissues form its lining, and nervous tissue forms a communicative extension throughout both its wall and its lining.” (4) Select any of the highlighted grid patterns on the surface of the organ and zoom in. The 3-D grid pattern becomes flattened, and a planar rotating model of one of the tissues of the organ comes into view. The text prompt: “A tissue is an organization of a great many similar cells with varying amounts and kinds of nonliving, intercellular substances between them. The variety of tissues comprise the organs, bones, and surfaces of the body.”
(5) Select any of the tiny grid points on the tissue model and zoom in. A rotating, oval-shaped model comes into view. Viewed as a wireframe model, numerous smaller shapes are seen inside. The text prompt: “Cells have long been recognized as the simplest units of living matter that can sustain life and reproduce themselves. The human body is said to contain some 1 x 10^14 cells, or, approximately 100 trillion cells. Inside each cell are various organelles which contribute to the cell’s functioning. Although the central nucleus inside each cell in the human body contains an exact copy of an individual’s DNA, cells perform a variety of different structural and functional tasks in the body.” (6) Select the densely-packed and intertwining string-shapes inside the nucleus of the cell model and zoom in. The string unwinds itself, straightening out into discrete segments. The text prompt: “Inside the nucleus of each human cell is found 46 densely packed chromosomes, 23 inherited from each parent.” One by one, each of the chromosomes is aligned in a grid format on the monitor, each appearing as a rough, string-shaped “X” character. The text prompt: “Each chromosome is a long, coiled, string composed of DNA (deoxyribonucleic acid).” One of the chromosomes unwinds itself. “The structure of DNA is that of a coiled double helix, akin to a spiral-shaped ladder. DNA consists of a long sequence of nucleotides, which are composed of three primary molecular elements: a sugar, a phosphate molecule, and one of four bases (Adenine, Thymine, Guanine, Cytosine). In genetic analysis, the particular sequence of nucleotides relates to the production of proteins, which then go on to perform a variety of biochemical functions in the organism. The human organism is thought to have some 80,000 genes, each gene composed of a sequence of DNA.” The chromosomes are then re-aligned in the grid and identified by a letter (A, T, C, G) signifying a particular nucleotide within the DNA sequence, within the chromosomal structure, within the cell. As this readout of nucleotides begins to scroll, it is made to match the readout on the margins of the monitor which relates the genetic code of the body being scanned, so that the information in each section is identical.
(7) Select the “Save As…” and then “Upload” commands. The genetic information (nucleotide sequences, position on chromosome, known coding information, known related protein structures) is saved onto a database. This file folder is then uploaded onto a remote FTP (file transfer protocol) server as a series of HTML documents for access via the Internet.
This sequence of analytical events, triggered by a set of hypothetical computerized tasks, is presented here in an intentionally constructive manner. The gradient from the anthropomorphic-corporeal body to genetic code is, nevertheless, one of the primary analytical assumptions which informs both contemporary anatomy and genetics textbooks, and it serves as a relational and differentiating function between these scientific practices. It is especially this differentiating character, along the assumed gradient from the macro- to the micro-biological, that these two significantly distinct modes of logic with respect to the body become more prominent. In other words, if the anatomical sciences proceed through an organizing logic of functional parts and wholes (and here, at the risk of becoming reductive, one could highlight continuities between Andreas Vesalius’s early modern anatomical texts and the informing principles of anatomy in medical imaging, surgery, and medical care generally), the “anatomizing” logics of genetics research privileges the relationships between a textuality of coding and the molecular mechanics of biochemical processes (transcription and translation of DNA into RNA, production of proteins, reverse transcription of DNA from RNA).
The question here is twofold. First, what are different logics or modes of knowledge-production by which molecular biology (in contrast to anatomy and physiology) approaches and organizes some object termed “the body”? Secondly, as a socially-embedded science with complex histories, how do specific forms of the body-language relationship (forms of textualization, taxonomic fragmentation, complex sign systems) contribute not only to the reproduction of scientific praxis itself, but also to the production of discrete units relating to the subject as a body? The first question has to do primarily with the ways in which a particular scientific practice maps out its terrain of research, establishing the issues, conceptual nodes, and problems that will be of concern. The second question has to do with the methodologies, techniques, and technologies involved in the processes of research, development, and practical (that is, medical and/or commercial) implementation.
The particular mode of textualization within genetics is qualitatively different from the constructivist logics of anatomical science. Working from the molecular level, the body as a whole or in parts is not an explicit part of the epistemology of genetic research. Classical and contemporary genetics do not anatomize the microbiological body, as they are concerned with the processes whereby the body on the biochemical and microbiological level is regulated, produced, and maintained as a series of information-transmission patterns. If the cell forms the essential unit of composition of the anatomical body, DNA does NOT analogously compose the genetic body. The genetic code – the particular sequence of nitrogenous bases which twist and turn to help form a given chromosome – is a linearly-arranged, complementary (Adenine always binds to Thymine, Guanine to Cytosine) “DNA text” based almost entirely on differential relationships. The letters which geneticists use to signify the sequence of bases (A for Adenine, T for Thymine, G for Guanine, C for Cytosine) form a combinatorial series which provides a blueprint for the production of a variety of amino acids (which, when chained together, form the structural and biochemical “building blocks” of proteins). When geneticists speak of a genetic code, most often what is referred to is the relationship between a given sequence unit and the production of an amino acid.
However, it is not exactly accurate to use linguistic or “text”-related tropes in discussing the genetic code, since DNA does not, strictly speaking, have a grammar. This non-grammatical textuality of DNA has undergone (and is undergoing) several changes since Mendel’s experiments with plant hybrids in the early part of the century. Most notably, it was James Watson and Francis Crick’s research during the 1950s on the structure and mechanics of DNA that helped to establish the specific “coding” character of genetic material. Watson and Crick explicitly made reference to the notion of “genetic information” rather than linguistic signs or a molecular linguistics. Yet, as many historians of science point out, this conception of DNA was fairly enclosed; DNA at this point (what physicist Erwin Schroedinger had earlier dubbed the “master molecule”) constituted a highly centralized, hierarchical information-operation distribution point which ran linearly from the genetic code to the processes it activated for protein production. In an extension of classical genetics, Watson and Crick’s model concerned itself with the transmission of units of genetic information, within the cellular processes of an organism as well as across generations of organisms. As a molecular structure based almost entirely on a multiplicity of differential, combinatorial relationships, the genetic “code” was more closely aligned metaphorically with the notion of data or information established by classical information theory and cybernetics.
This cross-disciplinary engagement with the notion of “information” was, still, only a partial investment in the way that information theory and cybernetics had defined information during the 1950s. During the same period, Claude Shannon and Warren Weaver, working at Bell Research Labs, developed their “mathematical theory of information,” which was primarily dependent on regarding information as a discrete quantity of signals (whether textual, electronic, digital, or even musical) independent of the quality or content of those signals. As Weaver pointed out:
The word information, in this theory, is used in a special sense that must not be confused with its ordinary usage. In particular, information must not be confused with meaning. In fact, two messages, one of which is heavily loaded with meaning and the other which is pure nonsense, can be exactly equivalent, from the present viewpoint, as regards information. 1
For Shannon and Weaver, information was a pattern, a particular organization in an inverse relationship to entropy, or the tendency of systems to degrade or become disorganized over time. Though Norbert Wiener’s notion of information in cybernetics (the study of communication and control in systems – machinic or organismic – based on feedback) contains some differences from that of Shannon and Weaver, Wiener too discusses information as “negative entropy.” Information theory was likewise conceived of as the “fundamental problem of communication,” which was concerned with “reproducing at one point either exactly or approximately a message selected at another point”2. In terms of Shannon’s research for Bell Labs, and as an important contribution to network-based research that led to the development of the Internet, information theory attempted to map out the highest possible statistical rate of successful transmission with the lowest possibility for unwanted or excess information, termed “noise.”
Given this perspective, Watson and Crick’s use of information with regards to DNA was primarily a metaphorical appropriation, as Evelyn Fox Keller points out. In contrast to information theory, the content or “meaning” of a particular DNA sequence was highly important for geneticists; a single point mutation or alteration in the genetic code would significantly affect a wide range of biochemical properties in the organism. Though all of this concerns an emerging paradigm of viewing organisms, machines, and other complex relationships in terms of communication and information processing systems, the apparent intersection of information sciences and molecular biology contained some important differences. Watson and Crick’s model differed, then, on the defining properties of what constituted information, as well as the mechanics of information as a process (linear transmission as opposed to cybernetics’ feedback loops).
However, with the emergence of new techniques and technologies in genetics and biotechnology research (beginning with the development of recombinant DNA in the 1970s) the relationship between genetics and informatics becomes a much more intimate, almost inter-disciplinary instance where the conceptual node of “information” is continually re-negotiated. A few brief examples:
Recombinant DNA: In 1973 American geneticists Herbert Boyer and Stanley Cohen performed the first successful transmission of a gene between two different organisms. Their experiments made use of two types of enzymes naturally occurring in micro-organisms, restriction enzymes and ligase enzymes, which, respectively, perform the cutting and stitching procedures of molecules within a DNA sequence. Using restriction enzymes, they isolated a gene for an antibiotic resistance and used the same restriction enzyme on DNA from an African clawed toad. They found that the restriction enzyme EcoR1 not only cleaved DNA at a specific site, but also synthesized the sticky ends required for the ligase procedure. After combining these fragments into the first recombinant use of a plasmid (bacteria), they used these bacterial cells to reproduce this recombinant gene. Cohen dubbed the replicating plasmid containing the spliced gene a “chimera,” and coined the term “recombinant DNA” to describe their technique of gene splicing. In 1980 they were granted a patent (the Stanley Cohen-Herbert Boyer patent applied for in 1974) for the technique of gene splicing.
Polymerase Chain Reaction (PCR): In the mid-1980s, a group of researchers working at the biotech startup company Cetus developed a technological methodology for the large-scale, automated production and analysis of DNA sequences. Called Polymerase Chain Reaction, this technology applied a series of heating and cooling cycles to a specified region of DNA. The heating cycle would weaken and break the bonds holding the double-stranded DNA molecule, at which time “primers” (beginning and ending molecules used for tagging specific sites on a DNA sequence) were added, followed by a Polymerase enzyme, which proceeded to synthesize complementary strands as the cooling cycle was initiated, forming two double-stranded DNA molecules from a single one. Once this procedure is repeated, the amount of the desired DNA sequence is exponentially amplified, making abundant “raw material” available for research. PCR was one of among many technique-technology hybrids which helped to contribute to the biotechnology boom of the 1980s, and in 1993 Kary Mullis was awarded the Nobel Prize in chemistry for his involvement with the development of PCR.
In terms of genetic information, the development of recombinant DNA techniques actually involves two distinct procedures. The first is that of intentionally (that is, as opposed to naturally occurring mutations in the genetic sequence) re-organizing DNA, either by producing transgenic types of organisms (a gene or genetic sequence transferred from one organism to another, as Cohen and Boyer did), or by introducing specially engineered sequences (DNA or RNA altered or prepared outside the organism) into the genetic sequence of an organism. The second procedure relates to the way in which the recombinant genetic sequence is or is not successfully integrated into the organism’s overall molecular and biochemical makeup. Sometimes this is accomplished through cell replication normally occurring in the organism, but often is done through cloning techniques, such as the use of plasmids to effectively mass-produce the recombinant sequence before being introduced into the organism.
As Paul Rabinow has stated, the invention of PCR not only changed and challenged genetics and biotechnology research, but it also constitutes a redefinition of how the organism is approached on the molecular level.
Genes were becoming manipulable biochemical matter. Khorana [a well-known researcher in genetic cloning] was trying to harness a biological process (polymerization) as part of a larger project to make an artificial version of a biological unit, a gene. Mullis’s decontextualization and exponential amplification was the opposite of Khorana’s efforts at the mimicry of nature. Mullis discovered a way to turn a biological process (polymerization) into a machine; nature served (bio)mechanics. 3
Though the polarization of nature/culture in Rabinow’s account might be nuanced, the relationship between the genetic engineering experiments of the 1970s and the development of PCR in the 1980s is significant. Much of genetic engineering (including recombinant DNA techniques, genetic cloning, and the use of restriction enzymes for cutting, ligases for stitching, and reverse transcriptases for the reverse production of DNA from RNA) had to do with the harnessing and concerted redirecting of “naturally occurring” biochemical processes at the molecular level. For example, restriction enzymes are often found as components of the immune system, identifying and attaching themselves to foreign elements (antigens) to be destroyed. The precision and specificity of restriction enzymes made them ideal tools for identifying, marking, and cutting at particular regions along the DNA molecule, making them one of the major tools for genetic engineering.
By contrast, PCR, in one sense, had nothing at all to do with genetics or biotechnology; it is, first of all, a little black box, a technological object designed for a specific (research-based, industrial, commercial) purpose. In another sense, though, it is a technology which develops concurrently with and which is specific to genetics and biotechnology research, and in this sense PCR technology follows upon the developments of other genetics/biotechnology-related machines available to laboratories during the 70s and 80s, such as spectrophotometers (often used for recognizing strong or denatured bonds in molecules) and DNA synthesizers (which automate the replicating and transcription processes utilized by genetic engineers). The fact that bio-technologies such as PCR produce biological components outside of an organic or organismic context, and that PCR applies computer-based technologies (such as “loop” programs designed to carry out repetitive tasks) towards processes not found in the organism, both suggest that a specific type of cyborgic or technoscientific relationship is being produced within the discourses and research of molecular biology. A genetically-engineered sequence of DNA (say, one coding for the production of a particular protein needed by the immune system), produced in a DNA synthesizer, “tagged” by radioactive molecular markers (so that researchers can follow the progress of the engineered sequence’s integration into the organism), amplified by PCR, then introduced into the genetic sequence of an organism – this is indeed a highly complex instance of the integration of machine and organism (or, better, of machinic and organismic logics) which Wiener emphasized as one of the primary focal points of his science of cybernetics in the late 1940s.
Recently, biotechnology and industry-related journals and networks (Recap, Biospace, Forbes Online) have noted a dual trend in the biotechnology industry: while the biotechnology boom of the 80s (rises in the stock of biotech startups, an influx of corporate investment and sponsorship, a growing research technology industry) has been declining in recent years, there has been an increase in the (only apparently new) field of “bioinformatics.” Generally speaking, bioinformatics relates to the application of information theory and information technologies to molecular biology research (specifically, genetic analysis and biotechnology). Bioinformatics forms a way to organize and articulate large amounts of genetic information in a way that may be useful for scientific research. The most prevalent use of bioinformatics has been the cataloging of genomic sequences from various organisms (including research produced through the Human Genome Project, and the genetic databasing projects of such corporations as GenBank), most of which are accessible over the Internet and Web. This type of databasing is both highly structured and flexible; it must facilitate access to genomic information and must also allow for modifications and additions to already-existing information. The databasing of genetic information allows for several types of research-based activity: (1) accessing and searching the database for particular genes and/or genetic sequences, (2) the development of techniques and methods for analyzing the production of amino acids and/or proteins from RNA sequences, (3) the comparative analysis of protein sequences, and (4) the development of techniques and technologies for working with molecular modeling and molecular structure.
As one particular example of the intersection between information theory and genetics, bioinformatics involves, first, the application of techniques of organization to data signifying molecular structures and relationships. From this perspective, information theory operates, as it does in its classical definition, indifferently to content; in the organization of information, greater emphasis is placed on the medium of information access (e.g., the Internet and computer databases) and the modes of logic through which access of information will occur (cgi-forms for searches, ftp procedures for downloading information). It is particularly in this last element (modes of logic that will frame information access) that the field’s relationship to the database will begin to matter. Certainly there are universal modes of database access (alphabetical, chronological, taxonomic), but in the case of bioinformatics, the mode of logic whereby the database will be accessed will depend upon how genetic information has been and is thought as an informational structure. Many searchable databases simply break down genetic information along the lines of how genetic information itself is organized in the organism, from the perspective of genetics and biotech research. That is, searches may proceed by specifying a particular chromosome, then by a particular region along each chromosome. Alternately, a search may be done for a specific sequence or gene without knowledge of its exact location, or searches may be done of all relevant genetic information pertaining to a particular disease or genetically related condition.
Generally speaking, then, bioinformatics applies in a redoubled manner the organization of information to genetic information (genomic sequences and genes) gathered through research. One question here, however, is to what extent this enframing action of information theory necessitates a reconfiguration within genetics of how genetic information is perceived. On the one hand, the information that comprises genetic sequences is still considered in a linear, sequential, and radically differential manner (the chain of nitrogenous bases comprising the DNA molecule). On the other, there is the process of informatics which treats units of information (here, sequences within DNA molecules) as a particular type of pattern defined through the perspective of genetics on how genetic information is reproduced, transmitted, and distributed in the organism.
Bioinformatics presents an instance where the already thoroughly textualized science of genetics is approached on an almost totally simulational level. This occurs in two, overlapping ways. First, in the translation of genetic research and its organization into a collection of integrated, interrelated, sign systems. For example, in protein analysis (studying the structures and relationships in the production of proteins from DNA), the DNA molecule, coded as a sequence of letters (ATCG), is put into an algorithmic program based on biochemical knowledge of protein structure and composition, and which can predict protein production, as well as the analysis of the protein being studied, which is equally presented as a series of letters (abbreviations for amino acids in a chain) with measurements relating the positions of particular molecules. All of this takes place at the dual level of genetic and software-based code.
The second way in which this redoubled textualization takes place is in molecular modeling. Often 3-D graphics programs are used to render and animate a given molecule, including color-coding schemes and multiple perspectives (ball-and-stick, full-volume molecules, chemical bonds, wireframe). Here technologies of visualization operate in a manner not unlike modern anatomy. A body (a molecular body) is recomposed using various diagrammatic strategies (superimposition of text, diagrams, color-coding) and is presented in a way in which it is isolated from any macro-context within the body. However, whereas anatomy depends upon and assumes the visual-representational referent of the visible, often dissected, corporeality of the human body, genetics is engaged in a structural-visual rendering activity which is equally about the production of a body. What is at stake in anatomy is the articulation and formal interpretion of the anatomical body. What is at stake in genetics is the composition and construction of a model, based less on visual-mimetic homologies than on the (biochemical, genetic) informational structure or pattern which composes a given molecule (e.g., a particular protein).
This is clearer by the standards of contemporary genetic research, which has moved away from the classical proposition put forth by Watson and Crick, among others, suggesting that DNA was the “master molecule” controlling and ordering all biochemical and genetic processes within the organism. From this centralized, nodal viewpoint, contemporary genetic research has moved towards a more distributed, networking model which de-emphasizes the functional autonomy of DNA, and highlights the multiplicity of parallel interactions within and outside the nucleus of the cell. As Manuel de Landa has suggested, this is a move towards viewing molecular processes within the organism as pattern relationships, rhizomatic networks, and “bifurcation” points which depend on the ways in which the organism at the molecular level functions and continues to produce itself as a complex system. Thus DNA by contemporary standards turns out to be relatively inert (it actually does nothing in itself), archival (it contains a great deal of molecular information that forms a kind of structural reference point for molecular processes), and partial (it is not an autonomous agent but interwoven into the molecular makeup of the organism).
The difficulty with all of this is that the abstractness of the relation of molecular biology and informatics to some notion of “the body” has become so tenuous that one is tempted to suggest the disappearance of that cultural-material construct the body in the face of these developing technosciences. Much of this is evident in media reports and anti-genetics publications, many of which approach and even assume the gene as an anatomical object, something akin to a limb or an organ. In cases concerning genetic patenting, to codify genes in this way is to violate an individual’s self and body, their genes being proper to the individual in the same way that an organ or limb is. But, rather than simply add to the already lengthy list of claims for the disappearance of the body, perhaps what is also at stake is the tenability – or rather “legibility” – of discourses encoding the body as corporeal, anthropomorphic, biologically sexed, and semi-autonomous with relation to the environment. In other words, there is no body to disappear with the application of informatics to genetics, for, at least since the 1950s, genetics and molecular biology generally have always been about considering the organism as an information-processing system. Despite the changes in genetic research since Watson and Crick’s conscious adoption of the information trope, the body that results from the complex intersection of genetics and informatics is primarily about the processes involving a range of discrete patterns of information within a flexible yet articulated network.
But if the category of the body is no longer tenable, perhaps the case is different with regards to what N. Katherine Hayles terms “embodiment.” Hayles suggests that embodiment is always at some proximity of difference to the “body,” where the latter is taken as that historically shifting hegemonic concept to which the former is never identical. In information theory terms, embodiment constitutes the noise differential of the body, and thus is also never prior to or external to those sets of normative constraints. Embodiment is, then, also a contextualized materialization; as scientific objects called genes, as informatic objects called databases, as communicative objects called networks. Thus, in looking at bioinformatics and its manifestations on the Internet, one primary question is how those databases and the networks they operate on relate to various notions of the body and embodiment; how “bodies” termed “genes,” “data,” “sequences,” “networks,” “organization,” and “databases” are all technoscientifically deployed, as well as how a range of possibilities constituting “embodiment” are equally enframed.
1. Shannon, Claude, and Warren Weaver. The Mathematical Theory of Communication. Chicago: Univ. of Illinois, 1965, p.8.
2. Ibid., p.31.
3. Rabinow, Paul. Making PCR: A Story of Biotechnology. Chicago: University of Chicago, 1996, p.9.
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