Biology Reference
In-Depth Information
Where is sequence likely to take biology in the near future? This
conclusion is an apt place to make some suggestions. Sequence is not
going away: next-generation sequencing machines are making more
and more sequence and more and more data an increasingly taken-for-
granted part of biology. The ways in which these increasingly massive
amounts of data are managed are likely to become ever more entan-
gled with the management of data in other domains, especially with
web-based technology. Bioinformatics will become just one of many
data management problems. These changes will have consequences
not only for biological work, but also—as the results of bioinformat-
ics are deployed in medicine—for our understanding of our bodies.
Computational approaches to biology may become so ubiquitous that
“bioinformatics”—as distinct from other kinds of biology—will disap-
pear as a meaningful term of reference.
Next Generations
Biological materiality is becoming ever more interchangeable with data.
Since 2005, so-called next-generation sequencing machines have given
biologists the ability to sequence ever faster and ever cheaper. In the
medium term, as these machines are sold to hospitals and companies
selling personalized genomic tests, this phenomenon is likely to have
a profound effect on medical care.
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However, these machines are also
likely to fi nd more use in basic biology, and here too, they are likely to
have profound effects on the production of biological knowledge. This
study of bioinformatics—in many ways a study of the speeding up of
biology—should prepare us to understand what the consequences of
next-generation sequencing may be.
Next-generation technologies (also called next-gen) were inspired
not only by the HGP—which demonstrated the commercial potential of
sequencing machines—but also by data-driven biology. If bioinformat-
ics, as we have described it here, is about high volume and high through-
put of data (especially sequence data), then next-gen is its technological
complement. Both the technology and the science itself can be said to
be driven by data. Each provides a further justifi cation for the other:
we need more and faster sequencing technology so we can amass more
data, and we need the statistical techniques of data-driven science in
order to digest those data into useful knowledge. So bioinformatics and
next-generation technologies go hand in hand and stand in a relation-
ship of mutual causation.
Moreover, next-generation sequencing seems to lie at a crucial in-
