Biology Reference
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13. Gilbert, “Towards a Paradigm Shift.”
14. Barnes and Dupré, Genomes . This view is also informed by the work of
Brian Cantwell Smith on problems of ontology in computer science. Smith, On
the Origin of Objects .
15. Although recently, increasing recognition of the value of data is chang-
ing this. For example, the journal Gigascience (launched in 2012 by the Beijing
Genomics Institute) will accept and host large-scale life science data sets in its
database. The aim remains, however, to promote and publish “studies” of these
data sets.
16. Nature , “Community Cleverness Required.” This editorial appeared as
part of a Nature special issue on “big data.”
17. Some representative examples from sociology and history: Appadurai,
Social Life of Things ; Schlereth, Material Culture ; Bourdieu, Outline : Miller,
Material Culture . Some representative examples from the history of science:
Galison, Image and Logic ; Kohler, Lords of the Fly ; Chadarevian and Hop-
wood, Models ; Rasmussen, Picture Control ; Rader, Making Mice ; Creager, Life
of a Virus ; Turkle, Evocative Objects .
18. Fortun, “Care of the Data.”
19. See Kohler, Lords of the Fly .
20. During 2007 and 2008, I conducted participant observation-style
fi eldwork at three locations: at the laboratory of Christopher Burge, in the De-
partment of Biology at the Massachusetts Institute of Technology, Cambridge,
Massachusetts; at the Broad Institute, Cambridge, Massachusetts; and at the
European Bioinformatics Institute, Hinxton, United Kingdom.
21. This is a good point at which to distinguish this account from Joe
November's very important historical accounts of the fi rst uses of computers in
biology (November, “Digitizing Life,” and November, Biomedical Computing ).
November's narrative begins with the fi rst computers developed in the wake
of World War II and concludes with the application of artifi cial intelligence
to biology at Stanford in the 1960s and 1970s. Here, I begin—for the most
part—in the 1970s and attempt to come as close to the present as possible. In
a sense, this account can be seen as a sequel to November's: even at the end of
the 1970s, computers were extremely rare in biology and medicine, and those
who used them remained far from the mainstream. To understand the ubiq-
uitous, seemingly universal role that computers have come to play today, we
need to understand what has happened with computers and biology since the
1970s.
22. Writing a history of bioinformatics is in some ways automatically an
ahistorical project: no one did “bioinformatics” in the 1960s or 1970s. Of
course, the sets of practices that became bioinformatics later on can be traced
to practices from those earlier decades, but the “founding” individuals were
funded by different sources, organized in different disciplines, published in
different journals, and understood their work as having signifi cantly different
aims. By tracing back these strands, I necessarily exclude or gloss over many
of the other ways in which computers were used to do biological work from
the 1960s onward. Bioinformatics is centered almost entirely on a relatively
narrow set of computation problems focused on DNA, RNA, and protein
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