For the fun of it, here are a few examples of definitions:

To understand complex biological systems requires the integration of experimental and computational research — in other words a systems biology approach. (Kitano, 2002)

Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations. (Ideker et al, 2001)

[…]the objective of systems biology [can be] defined as the understanding of network behavior, and in particular their dynamic aspects, which requires the utilization of methematical modeling tightly linked to experiment. (Cassman, 2005)

By discovering how function arises in dynamic interactions, systems biology addresses the missing links between molecules and physiology. Top-down systems biology identifies molecular interaction networks on the basis of correlated molecular behavior observed in genome-wide “omics” studies. Bottom-up systems biology examines the mechanisms through which functional properties arise in the interactions of known components. (Bruggeman and Westerhoff, 2007)

Why is it so difficult to come up with a concise definition of systems biology? One of the reasons might be that every definition has to respect a delicate balance between “the yin and the yang” of the discipline: the integration of experimental and computational approaches (Kitano, 2002); the balance between genome-wide systematical approaches (Ideker et al, 2001) and smaller-scale quantitative studies (Tyson et al, 2001); top-down versus bottom-up strategies to solve systems architecture and functional properties (Bruggeman and Westerhoff, 2007). But despite the diversity in opinions and views, there might be two main aspects that are conserved across these definitions: a) a system-level approach attempts to consider all the components of a system; b) the properties and interactions of the components are linked with functions performed by the intact system via a computational model. This may in fact reveal another source of difficulty when trying to define systems biology, which is to find a general and objective definition of “biological function” (or Lander’s “goal of the system”, see our brief post Teleology and Systems Biology). Feel free to comment and suggest on this…

In any case, rather than trying too hard to draw conceptual boundaries with theoretical definitions, I thought it would be interesting to see how the field defines itself. I introduced all the original research articles published in Molecular Systems Biology into del.icio.us and tagged the entries to have an idea of the distribution of several aspects of the research we publish. Inevitably my tags have rather broad meanings and the boundaries are often fuzzy (eg what is a “mechanism”?), but I tried my best by taking into account the following dimensions:

• scale of the study: genenome-wide vs small scale or single-cell, etc
• biological approach: transcriptomics, proteomics etc…
• computational approach: simulation, data-driven correlation model, network structural model, etc…
• insight gained: dynamics of the system, global properties (modularity, robustness, evolvability…), mechanistic insight, etc…

Here is the result, as a “tag cloud”

There is a clear, and not too surprising, dominance of genome-wide ‘omics’-type of studies (in particular transcriptomics). But it is also good to see that the small-scale studies, often using quantitative approaches and focusing on systems dynamics are also well represented. Again, this classification is very crude and somewhat arbitrary, but it provides nevertheless, at a glance, an overview of the landscape of systems biology. If I find the time, I will try to refine the concepts and introduce our content in a more structured way into freebase. Finding a structured way to characterize the “insight” of a study might be particularly challenging but it could be an instructive exercise.