Explanation in Biology

Volume 11 of the series History, Philosophy and Theory of the Life Sciences pp 249-264

Explanation and Organizing Principles in Systems Biology

  • Tobias BreidenmoserAffiliated withSystems Biology and Bioinformatics Group, University of Rostock Email author 
  • , Olaf WolkenhauerAffiliated withDepartment of Systems Biology & Bioinformatics, University of RostockStellenbosch Institute for Advanced Study, Wallenberg Research Centre at Stellenbosch University

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While explanation in biology is a well-established topic in philosophy of science, since the rise of new mechanistic approaches little has been said about explanation in Systems Biology. In this contribution, we analyze whether contemporary conceptualizations of explanation fit with the scientific practice of systems approaches in molecular and cell biology. We discuss how current views on mechanistic explanation can be applied to the use of mathematical models in system biology. To this end it is important to distinguish different kinds of models: While some of them merely save the phenomena, not being explanatory, others make mechanistic claims and can be embedded in the framework of mechanistic explanations. We will make a conceptual distinction and discuss the roles different kinds of models have in Systems Biology. In our view, the current mechanistic framework is not sufficient to capture all types of explanations occurring in Systems Biology. A multicellular system is not merely defined by its structural components, including genes, proteins and their interconnections, but has a functional organization, that is the system’s behavior, which emerges from its structural organization. Such emergent properties cannot be understood or explained by merely describing the mechanisms of the underlying molecular and cellular processes. We argue that organizing principles in Systems Biology provides a way of explaining such high-level system properties. With the help of a case study we show that organizing principles explain system-properties complementary to mechanistic explanations. They cannot replace them but they also cannot be reduced to them.


Systems biology Models in science Mechanistic models Mechanistic explanation Organizing principles Robustness