J. Biomedical Science and Engineering, 2009, 2, 78-79
Published Online April 2009 in SciRes. http://www.scirp.org/journal/jbise JBiSE
Systems Biology: The take, input, vision, concerns
and hopes
Graeme Tucker1
1Lighthouse Laboratories, SABC Loneragan Building, Murdoch University, South Street, Murdoch, Western Australia 6150. Correspondence should be ad-
dressed to Graeme Tucker (gtucker@lighthouselabs.org.au).
Received Jul. 4th, 2008; revised Mar. 1st, 2009; accepted Mar. 9th, 2009
Systems Biology is a relatively new branch of
biology that brings together an interdisciplinary
team of scientist, computer engineers and
mathematicians. Biomedicine can gain much
from the input of Systems Biology. The object
and aims of this article centre on clarification
and direction for Systems Biology, notably in
regard to human health and disease.
The take: Many consider today’s Systems Biology as an
incarnation that was instigated by the biotechnological
revolution of high throughput data acquiring instruments.
Data gathering and processing, emerged with two
streams: refinement during the gathering stage or, re-
finement at the point of analysis. However, the rapid
development of this high throughput hardware was
missing the resources to decipher the vast amounts of
data produced. Handling of such data required the adap-
tation of computational platforms and users. The user(s)
emerged as an interdisciplinary cross breed of research-
ers: mathematicians, computer specialist and to a lesser
extent the biologist, because of skill displacement. An
immediate challenge for this new breed of researcher
was defining Systems Biology. Initial workers reflected
upon their activity for inspiration: informatics
/computational biology demonstrates the ‘relativity’ of
biological composite by use of ‘networking’ illustrations
supported by software programs and mathematics. Con-
sideration with regard to this form of data representation
closely resembled their engineering heritage; in particu-
lar Control Systems. Thus, the word ‘System’ had rele-
vance. Because the theme related to Biology the phrase
Systems Biology was coined.
However, a decade on there is still controversy sur-
rounding the definition of Systems Biology and what it
means to a broad spectrum of researchers in their daily
activities. Rightly or wrongly the biologist and philoso-
pher is at risk of being displaced from the driving seat of
biological research. Computology could function as a
new word to describe the computer and mathematical
specialist engaged in biology. Aside from those resisting
change, many traditional biologist have reacted to this
branch of biology as a branch lacking turgidity. Others
argue that their wet medium for research is now waters
muddied by Systems Biology. Advocates of Systems
Biology from all camps continue to seek clarification
and as such new definitions are regularly floated as ves-
sels to carry Systems Biologists on their voyage of dis-
Input: In a diffuse setting Systems Biology in one sen-
tence could be described as follows: ‘Systems Biology is
a branch of biology that is an interjection of fields and
disciplines, with applications collectively integrating
broadly acquired data from all research levels for the
purpose of indicating or modelling phenotype. ’
A definition of Systems Biology in one word could
possibly be, ‘Relativity’. Nature complies with the law
of physics and physical things are superimposed on
mathematical principles. This can include stimuli such as
the fight or flight response or, sexual arousal.
Of particular interest and relevance, is the notion that
the Systems Biologist will consider and address their
challenge beyond the immediate viewpoint of the bio-
logical composites of interest.
The term ‘Model’ is frequently used in context of Sys-
tems Biology. A model is a representation of a fea-
ture/function; a condition that is simulated or, a compos-
ite that is mimicked. That representation need not nec-
essarily be a biological attribute. For example an intrin-
sic or extrinsic stressor (infection or sun stroke) can lead
directly to a physical affect (fever or hyperthermia).. In
an indirect setting such as arachnophobia, consideration
is given to memory, psychological predisposition and
reflex. An example of a traditional model for a biologist
is an organism such as yeast or, the mouse. A model for
the computer engineer is a software program; a model
for a mathematician is an equation. Thus, computation
serves to ‘simulate,’ mathematics serves to ‘mimic’ and
biology serves to ‘feature.’ Together, they serve Systems
Biology. From a retrospective perspective the phrase is
perceived as an encompassing mode or stage. From an-
other perspective, Systems Biology is a language, a
script and an instrument. In many respects it is the mir-
rored reflection of Biological Systems in the literal
Vision: In the not too distant future it is suspected that
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Systems Biology will be a prerequisite of project plan-
ning for wet based laboratory research, much in the same
way that consideration of ethics is a necessity for re-
search endorsement and support.
Concerns: Wet laboratory research has had the in vitro
model for many years. For the researcher it has proved
unambiguous in distinguishing the significance and rela-
tivity of outcomes to that of the in vivo setting. However,
with the emergence of the in silico model the risk of
ambiguity is clearly present. Of particular concern is that
wet lab ‘fact’ is fiction-ated (in silico) and that the sub-
sequent fiction outcomes, after model manipulation /
extrapolation, are inferred as fact in the bigger picture of
true fact. In that setting the audience of communicated in
silico science is at risk of having their own works mis-
guided, notably the wet laboratory researcher. Therefore
is the informatics camp muddying the waters of wet lab
In addition, is in silico science operating with aseptic
techniques when fact-ors are introduced in the extrapola-
tion process? Is there a risk of fashioning fact to the
point of becoming arte-fact?
Equally, is there a risk of fashioning wet laboratory
experiments to fit the predicted in silico assumptions?
Hopes: Systems Biology needs some standardisation
policies and techniques to ensure that the concerns out-
lined above are not encountered.
The incorporation of Systems Biology principles in
project planning will hopefully have the benefit of mini-
mising and reducing calculated aspects such as cost and
risk. However, in the spirit of far reaching science (true
philosophy), which is usually accompanied by risk, it is
hoped that this reach is not compromised; if anything, it
is hoped that Systems Biology will gather the pace and
direction of research.
Turnaround benefits shall hopefully be seen in
medicine (facilitation of modes for the prevention,
diagnosis, treatment and cure of disease), agriculture
(increased crop yield, crop resistance and crop toler-
ance) and in the development of sustainable energy
through bio-fuels.
Beyond Systems Biology is Systems Life.
Can it factor in consciousness and meaning?