The reductionist approach to Biology is based on dividing biological systems on their constituent parts, e.g., molecules in the case of Molecular Biology, and then studying these parts in isolation to finally infer the properties of the system as a whole. This strategy thus proposes that any aspect of a living system can be ultimately explained by the functional knowledge of its constituents, and that the fact that we can not explain some biological phenomena today is only due to our current limited information of its ingredients.

Indeed, the reductionist agenda has been extremely successful in explaining many aspects Biology, as when applied to other areas of Science. Nevertheless, it is clear than some functional characteristics can not be analyzed by reduction. This is because biological systems are the prototype of a more general class of complex systems, where the non-linear interactions between their components makes impossible to understand system function as merely the sum of the parts. The essential notion here is that the impossibility to predict high-level properties from the constituents information is not due to our probable limited knowledge of the constituents, but rather to something inherent to how the elements work as a system.

While in other areas of Science the reductionist approach was long ago complemented by systemic approaches -an every-day example being Meteorology- the tremendous inertia of Molecular Biology made reductionism dominate research in Biology until very recently. Today, it is however clear that many biological phenomena could never be fully understood from the study of the properties of the molecular components only. The whole is not a mere sum of the parts but a more complex (non-linear) function of them. Among the (complex) biological systems which escape a reductionist explanation those involved in pathogenic states are of particular relevance.

In this way, Systems Biology emerges as a balancing alternative to Molecular Biology. Systems Biology approaches biological phenomena by integration, instead of reduction. In a representation of biological phenomena where the molecular components are at the bottom, i.e., molecular → cellular → organismal → ecological → …, Molecular Biology follows a bottom-up strategy (studying low-level phenomena to understand higher level ones), while Systems Biology follows a top-down one. In this systemic view, the biological information is not obtained from the detailed properties of the pieces but from higher levels of complexity (i.e., network of relationships between these components).

Systems Biology is then a combination of a field of study, a change in paradigm, and a novel methodology. As the latter, it involves many approaches, such as the -omics (genomics, proteomics, transcriptomics, etc) for obtaining the repertories of components and their relationships in a systemic (high-throughput, non-detailed) way; quantitative mathematical modeling (this including mathematical evolutionary models); network biology (emergent properties of networks of biological relationships); non-linear Dynamics and Statistical Mechanics (with the application of a new language based on information processing circuits), etc.

The greatest task of understanding biological systems is probably to apply the right level of description on each phenomenon within the complexity pyramid. It is clear that only by attacking Biology from the two fronts (top-down and bottom-up) we will ever be able to fully understand many biological functions, and in particular how problems in function eventually lead to disease.

Systems Biology in Wikipedia

Van Regenmortel. Reductionism and complexity in molecular biology. Scientists now have the tools to unravel biological and overcome the limitations of reductionism. EMBO Rep (2004) vol. 5 (11) pp. 1016-1020

Nurse. Systems biology: understanding cells. Nature (2003) vol. 424 (6951) pp. 883

Kitano. Systems biology: a brief overview. Science (2002) vol. 295 (5560) pp. 1662-4

Systems Biology Program @CNB-CSIC

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