A plea for more theory in molecular biology.
The integrationist principles of systems theory have proven hugely successful in the physical sciences and engineering. It is an underlying assumption made in the systems approach to biology that they can also be used to understand biological phenomena at the level of an entire organism or organ. Within this holistic vision, the vast majority of systems biology research projects investigate phenomena at the level of the cell, with the belief that unifying principles established at the most basic level can establish a framework within which we may understand phenomena at higher levels of organization. In this spirit, and to use a celestial analogy, if a disease--effecting an organ or entire body--is our universe of discourse, then the cell is the star we gaze at. In building an understanding of disease and the effect of drugs, systems biology makes an implicit assumption about direct causal entailment between cell function and physiology. A skeptic might argue that this is about the same as trying to predict the world economy from observations made at a local supermarket. However, assuming for the moment that the money and hope we are investing in molecular biology, genomics, and systems biology is justified, how should this amazing intellectual achievement be possible? In this chapter we argue that an essential tool to progress is a systems theory that allows biological objects and their operational characteristics to be captured in a succinct yet general form. Armed with this conceptual framework, we construct mathematical representations of standard cellular and intercellular functions which can be integrated to describe more general processes of cell complexes, and potentially entire organs.
Wolkenhauer
O
O
Systems Biology and Bioinformatics Group, University of Rostock, Germany. wolkenhauer@informatik.uni-rostock.de
Mesarović
M
M
Wellstead
P
P
D019295:Computational Biology; D004247:DNA / Q000737:chemistry; D023281:Genomics; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D008967:Molecular Biology / Q000379:methods*; D011506:Proteins / Q000378:metabolism; D012333:RNA, Messenger / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*
D011506:Proteins; D012333:RNA, Messenger; D004247:DNA