EMBO reports  VOL 10 | SPECIAL ISSUE | 2009 ©2009 European Molecular Biology OrganizationS46
science & societyscience & society
Calculating life?
A sociological perspective on systems biology
Jane Calvert & Joan H.Fujimura
S
ystems biology is an excellent research
topic for social scientists because systems
biologists themselves are fascinated
by the social organization of their
field. Moreover, as systems biology is an
emerging research area, studying it from a
sociological perspective allows social scientists
to observe how scientists develop new
fields of inquiry and practice, and challenge
existing institutional and disciplinary structures.
This article presents the results of our
study of systems biology and of how systems
biologists perceive their own field.
We start by exploring the organization of
knowledge production in systems biology,
which is a research ‘approach’ that brings
together biologists, physicists, engineers,
mathematicians and computer scientists in
novel interdisciplinary arrangements. We
then look at how systems biology positions
itself in relation to other types of biological
inquiry, particularly molecular biology.
Discussions of the distinctiveness of systems
biology often address the goals of the
field: some systems biologists aim to make
biology as quantitative, rigorous and predictive
as physics and engineering, with the
overall objective of making living systems
calculable and ultimately predictable; others
argue that this aspiration is misplaced, and
stress the contingency and unruliness of biology.
We explore these tensions, and reflect
on their sociological dimensions and their
consequences for future interdisciplinary
work in the life sciences.
This article presents results from our
empirical research. We draw on more than
50 interviews with systems biologists from
the USA, UK and Japan, as well as attendance
at systems biology conferences and
workshops, extended visits to laboratories
and discussion groups with systems biologists.
Although we refer to our respondents
by their discipline of training, they all selfidentify
as doing systems biology.
S
ystems biology is usually described as
an attempt to make sense of the vast
amounts of data that have been generated
by genome-sequencing projects and
other molecular data-generating exercises.
System biologists develop and use algorithms,
software and mathematical models to
analyse the data in order to produce dynamic
insilicomodelsofbiologicalsystems.Systems
biologists either are, or have recruited to their
enterprise, physicists, computer scientists,
engineers and mathematicians.
As with many new research fields, there
is as yet no consensus definition of systems
biology. Systems biologists argue, however,
that the novelty of their field arises from the
kinds of computational technologies that
are being used to study biological systems,
which have made it possible to accumulate
and analyse previously unprecedented levels
of molecular data, and have allowed the integration
of many different types of data. Our
interviewees often said that systems biology
is an ‘approach’, rather than a traditional
research discipline. In fact, one of its key features
is interdisciplinarity, which interviewees
described as necessary to solve the problems
that are being raised by the field.
It is notable that systems biologists
articulate a division between the ‘social’
and ‘scientific’ elements of their field, and
then openly discuss the value of the social
aspects. This is in part because they work
in a situation that differs significantly from
the more common way of doing science in
the past century. Instead of working within
disciplinary boundaries, systems biologists
see their research as transgressing these
boundaries. They attempt to integrate not
only data and technologies, but also disciplines
and people. Scientists talk about
how “the development of systems biology
depends on the sociology” and how it is
important to cultivate a social environment
in which scientists with different expertise
can work together productively.
A
nother demonstration of the interconnectedness
of the social and
the scientific is the commonly
expressed idea that systems biology has ‘no
walls’. This point is made in a metaphorical
sense: systems biologists maintain that the
field draws on expertise from whichever
area is most useful or appropriate at the time
because “ideas are everywhere”, as one
interviewee noted. Two senior researchers
even thought that the disciplinary spread
of systems biology could extend to the
social sciences and humanities. The idea
of ‘no walls’ also has currency in a literal
sense because there are no walls between
the laboratories at many systems biology
institutes, in order to facilitate communication
between researchers. New buildings
have interdisciplinarity purposely built
into the design, with social spaces where
the ‘wet’ experimental people and the ‘dry’
…some systems biologists aim
to make biology as quantitative,
rigorous and predictive as
physics and engineering…
…systems biologists maintain
that the field draws on expertise
from whichever area is most
useful or appropriate at the time
because“ideas are everywhere”…
©2009 European Molecular Biology Organization EMBO reports  VOL 10 | SPECIAL ISSUE | 2009 S47
science & societyspecial issue
computational people can easily come
across one another.
It is not easy to establish such new
institutional arrangements. Leroy Hood,
Director of the Institute for Systems Biology
in Seattle (WA, USA), said that he had to
fight against the constraints of academic
bureaucracy to set up his new research
institute (Agrawal, 1999). Similarly, Hiroaki
Kitano, who established The Systems
Biology Institute in Tokyo, Japan, built his
institute outside the university system. This
also meant, however, that he faced some
difficulties related to working outside the
usual academic networks. Another example
is the development of an interdisciplinary
systems biology centre in the UK, which
required “an enormous struggle” according
to a British biologist, because of vested
interests and conservative colleagues.
Hood’s view is that “new organizational
structures were needed for the realization
of a paradigm change” (Hood, 2008);
so, it might be that one way in which systems
biology can be distinguished from
the life sciences that preceded it is by its
organizational innovations. In its early days,
molecular biology was the product of a confluence
of scientists from several disciplines,
including biology, physics and chemistry.
This confluence became a discipline that
later transformed most of biology. Whether
something similar happens with systems
biology remains to be seen. Nevertheless,
even those who are reluctant to talk about
‘paradigm change’ in systems biology point
out that its most notable aspects include
its interdisciplinary nature, and the way in
which it has brought in a new wave of physical
scientists and mathematicians to study
biological issues (Noble, 2007).
M
any systems biologists have revolutionary
ambitions for their field,
which is often described by its
proponents as a new way of doing science
that will bring great changes. For example,
one computer scientist said that “we [are]
going to have to create a new way of thinking
about biology that’s going to be as great a
revolution as the molecular revolution was”.
As it makes a point of distinguishing itself
from previous research traditions, the question
of whether systems biology constitutes
a paradigm shift is often raised. Rather than
discussing the merits of the arguments about
paradigm shifts here, we look instead at how
and when the language of paradigms is used
by systems biologists.
The issue of whether systems biology
constitutes a paradigm shift comes up most
often in comparisons with molecular biology.
In fact, Fred Boogerd and colleagues
note that “practicing systems biologists
are often hindered by paradigm battles
with molecular biologists” (Boogerd et al
2007). A computer scientist highlighted
the antagonism between the two fields by
saying “it’s still very much an ‘us and them’
thing between the molecular and the systems
people”. This is in a context where,
until recently, “the mainstream was dominated
by the reductionist molecular biology
agenda”. Against this background, it is perhaps
not surprising that systems biologists
often experience resistance from the ‘old
school’ of molecular biology. Indeed, some
interviewees argued that the antagonism
towards systems biology from the proponents
of previous paradigms is itself a sign
of a paradigm shift.
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The most common way in which systems
biologists distinguish their work from that of
molecular biologists is by invoking the term
‘reductionism’, and arguing that systems
biology adopts a more holistic approach.
Interviewees said that systems biology studies
the system as a whole, rather than individual
molecules; this means that it is impossible to
study a system in terms of a ‘favourite molecule’,
which is a common characterization
of how a molecular biologist proceeds. For
example, systems biologists say that the normal
research training process in molecular
biology in the past was ‘one gene, one PhD’.
M
any systems biologists say that their
field is not reductionist and is in
fact a reaction to the essential failure
of the reductionist agenda, particularly in
terms of drug development, but also in terms
of the failure of reductionist approaches to
provide a satisfactory understanding of the
operation of biological systems. One biologist
put this point vividly by saying that systems
biology is “the name of the crisis; it’s
the name of the fright that every­one’s gone
into about having all the pieces and still not
knowing how biology works.”
The relationship of systems biology to
reductionism is not straightforward, however.
Some systems biologists are explicit
about their own reductionist objectives.
One, for example, thinks that “the systems
stuff’s really a starting point for the reductionist
biology.” Some commentators also
see systems biology as being firmly a part of
the reductionist enterprise, and the field is
even sometimes accused of being reductionism
writ large (Huang, 2000). There is also
the potential for a different type of reductionism
in systems biology: the application
of models from physics, mathematics and
engineering to biological data (Fujimura,
2005). In fact, a UK policy-maker warned
systems biologists at a conference that they
must be careful not to replace molecular
reductionist approaches with mathematical
reductionist approaches.
Despite these concerns, the dominant
discourse of systems biology is one of antireductionism.
This is so pervasive that the
Biotechnology and Biological Sciences
Research Council (BBSRC; Swindon, UK), the
largest funder of systems biology in the UK,
felt the need to state that it “has not become
anti-reductionist as a result of encouraging
theuptakeofsystemsbiologyapproaches[…]
the molecular-level research it has funded—
and continues to fund—is an important part
of the picture” (BBSRC, 2006). Although it is
not possible to distinguish molecular biology
from systems biology clearly in terms of
reductionism, systems biologists draw on this
representation of molecular biology when
they define their work in opposition to more
‘traditional’ forms of biological research.
A
nother way in which systems biology
is distinguished from molecular
biology is in its aspiration to make
biology a more rigorous and quantitative
discipline. For example, one interviewee
maintained that the “intuition or naive
understanding” of molecular biology will
be replaced with the “rigid mathematical or
computational understanding” that systems
biology brings. A UK systems biologist has
similarly written that “a key challenge for
the future is to integrate analytical tools,
technologies and theoretical rigour from the
physical sciences, engineering and mathematics
into the very fabric of bioscience
research” (McCarthy, 2004). The aim to find
foundational truths, laws or mathematical
structures in biology was expressed by
an ex-physicist, who said that he prefers to
do science “from a quantitative, theoretical
physics point of view” and is looking for
“equivalent laws and theoretical structures
in biology”.
A related feature of systems biology that
is also found in the physical sciences and in
engineering is the objective to be predictive.
Some systems biologists say that their ultimate
goal is to generate models in silico that
will be able to predict the emergent properties
of living systems. They think that once
this happens, life “will become calculable”
(Boogerd et al, 2007) and systems biology
will have fulfilled its promise.
A research field that specifically aims to
build biological systems that can be calculated,
modelled and predicted is synthetic
biology. Several interviewees discussed synthetic
biology and its relationship to systems
biology, and this comparison helps to illuminate
further aspects of systems biology.
The two can perhaps be most easily distinguished
in terms of their different intentions.
Whereas synthetic biology aims at construction,
systems biology is directed towards
understanding existing biological systems.
However, this distinction is not clear cut.
Steven Benner and Michael Sismour, for
example, stress how a greater understanding
of biological systems can be gained from
synthetic approaches (Benner & Sismour,
2005), and others see synthetic biology as a
way of testing the models in systems biology
by trying to build them as functioning biological
systems (Barrett et al, 2006). In this
way, synthetic biology can be described as
‘systems biology in reverse’, although some
see synthetic biology as a distinct field with
autonomous aims (Endy, 2005).
A clear objective of synthetic biology is
to make biology into an engineering discipline
(Endy, 2005). As in systems biology,
this is an attempt to make biology less qualitative
and descriptive, and more quantitative
and predictive (Lazebnik, 2002). Notably, in
both systems biology and synthetic biology
we see biologists trying to turn biology into
a ‘hard’ science.
H
owever, in both systems biology
and synthetic biology there are
those who think that this ‘hard’science
approach will not lead to biological
insight. Some scientists we interviewed
who are working in systems biology think
that the search for laws is misguided
because, as one computer scientist argued,
biology itself is more suited to the attitude
of the naturalist than the mathematician. He
explained that “[t]he naturalist is someone
who places a great deal of attention [on] the
oddity and the variety and multiplicity of
the world as it is.” He is sceptical of the idea
that biology is written in the language of
mathematics, and thinks that attempts to
find foundational truths in biology are mistaken.
Others agree that it is futile to seek
the kind of generalized ‘understanding’ that
would be gained from the discovery of general
laws, saying that, though, systems biologists
should think in terms of answering
specific biological questions.
In synthetic biology, we see similar concerns
about the application of principles
from engineering. Adam Arkin and Daniel
Fletcher, for example, have asked: “Can
Many systems biologists say that
their field is not reductionist
and is in fact a reaction to
the essential failure of the
reductionist agenda…
…in both systems biology
and synthetic biology we see
biologists trying to turn biology
into a‘hard’science
©2009 European Molecular Biology Organization EMBO reports  VOL 10 | SPECIAL ISSUE | 2009 S49
science & societyspecial issue
we develop, or deal with, the lack of a
coherent theoretical and physical foundation
for living systems? Or is control of
biology destined for the same fate as
rainmaking?” (Arkin & Fletcher, 2006).
Despite the attempts to integrate theoretical
rigour “into the very fabric of bioscience
research” (McCarthy, 2004), we might
never reach a situation where we have an
“Ohm’s law of genes and proteins” (Pleiss,
2006). Some interviewees think that biological
systems will not be fully susceptible
to engineering goals.
These differences in aspiration reflect,
to some extent, the differences between
the disciplinary backgrounds of the people
who are doing the research. For example, an
engineer pointed out that, in his experience,
engineers are always looking for general
principles, whereas biologists are far more
interested in the outliers. A computer scientist
agreed that “the biologist is always interested
in the particular and the oddity”; this
is perhaps because biologists are used to
working with “dirty, unruly living systems”.
Possibly because of these interdisciplinary
tensions, many systems biologists stress
the centrality of biology to their work. For
example, one biologist maintained that “the
really key point is that systems biology is
driven by biology.” Another insisted that, in
systems biology, “the questions are biology
and the language is biology.” Perhaps it is
because systems biology, with its emphasis
on computation and mathematics, is different
from biology as traditionally practiced
that these researchers want to emphasize
their commitment to biological questions.
A
lso, although a great deal of emphasis
in systems biology is placed on
computational modelling, most systems
biologists think that there is still—and
will be for the foreseeable future—an essential
role for ‘wet’ experiments that are carried
out at the laboratory bench. As one respondent
noted, “you’ve still got to do experiments
to prove that you’re correct.” This is a
demonstration of the point that it is hard for
many biologists, particularly those trained in
molecular biology, to accept the results of
computational experiments without doing
the ‘real’ biology (Calvert, 2007; Fujimura,
2003). A computer scientist working in systems
biology expressed this sentiment, perhaps
with some frustration, saying “I think
that the traditional approach has been that if
you don’t do it in a lab with a test tube and a
Bunsen burner, it’s not science.”
The importance of biology that is
expressed here is also seen in the views of
interviewees who think that systems biology
is not a paradigmatic change, but rather an
inevitable natural progression towards biological
understanding. One policy-maker
made this point by saying “I don’t think systems
biology is revolutionary as a direction
or as a vision, it’s just necessary,” whereas a
biologist expressed the view that “biology is
not different, biology is just more complex.”
Yet, we have shown that in many ways
biology is different. Systems biology attempts
to integrate data and ideas from several disciplines
in order to explore questions that
have not been answered by any single one.
This makes it different from molecular biology
as it has been practiced during the past
30 years. Systems biology also differs from
physiology in the twentieth century, not
least because it uses new technologies and
new forms of data. We have also shown that
there are many sociologically and philosophically
interesting features of systems
biology, such as the efforts to characterize its
practices in opposition to molecular biological
reductionism and to frame its aspirations
in terms of the ‘rigour’ of physics, mathematics
and engineering. Systems biology
brings together a range of different people
with different ideas about the nature of biological
understanding, and it transgresses
the boundaries between different scientific
disciplines. Whether these differences will
eventually constitute a paradigmatic shift
awaits an historical answer.
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…engineers are always looking
for general principles,whereas
biologists are far more interested
in the outliers
Some interviewees think
that systems biology is not
a paradigmatic change,but
rather an inevitable natural
progression towards biological
understanding
Jane Calvert (left) is a Research Fellow at the ESRC
Innogen Centre,Institute for the Study of Science,
Technology and Innovation (ISSTI),University of
Edinburgh,Scotland,UK.
E-mail: jane.calvert@ed.ac.uk
Joan Fujimura is a Professor in the Department of
Sociology and the Holtz Center for Research on
Science and Technology,University of Wisconsin-
Madison,WI,USA.
E-mail: fujimura@ssc.wisc.edu
doi:10.1038/embor.2009.151