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Catalyzing Inquiry at the Interface of Computing and Biology
to the forefront in the second half of the 20th century. These threads were biological experimentation and the search for the underlying mechanics of life.
Biological experimentation and the collection of data are not new, but they acquired a new importance and centrality in the late 20th century. The identification of genes and mutations exemplified by experiments on Drosophila became an icon of modern biological science, and with this a new focus emerged on collecting larger amounts of quantitative data.
Biologists have always been interested in how organisms live, a question that ultimately comes down to the very definition of life. A great deal of knowledge regarding anatomy, circulation, respiration, and metabolism was gathered in the 18th and 19th centuries, but without access to the instruments and knowledge of biochemistry and molecular biology, there was a limit to what could be discovered. With molecular biology, some of the underlying mechanisms of life have been identified and analyzed quantitatively.
The effort to uncover the basic chemical features of biological processes and to ascertain all aspects of the components by way of experimental design will continue to be a major aspect of basic biological research, and much of modern biology has sought to reduce biological phenomena to the behavior of molecules.
However, biological researchers are also increasingly interested in a systems-level view in which completely novel relationships among system components and processes can be ascertained. That is, a detailed understanding of the components of a biological organism or phenomenon inevitably leads to the question of how these components interact with each other and with the environment in which the organism or phenomenon is embedded.
2.1.3Biological Components and Processes in Context, and Biological Complexity
There is a long tradition of studying certain biological systems in context. For example, ecology has always focused on ecosystems. Physiology is another example of a life science that has generally considered biological systems as whole entities. Animal behavior and systematics science also considers biological phenomena in context. However, data acquisition technologies, computational tools, and even new intellectual paradigms are available today that enable a significantly greater degree of in-context understanding of many more biological components and processes than was previously possible, and the goal today is to span the space of biological entities from genes and proteins to networks and pathways, from organelles to cells, and from individual organisms to populations and ecosystems.
Following Kitano,1 a systems understanding of a biological entity is based on insights regarding four dimensions: (1) system structures (e.g., networks of gene interactions and biochemical pathways and their relationship to the physical properties of intracellular and multicellular structures), (2) system dynamics (e.g., how a system behaves over time under various conditions and the mechanisms underlying specific behaviors), (3) control mechanisms (e.g., mechanisms that systematically control the state of the cell), and (4) design principles (e.g., principles underlying the construction and evolution of biological systems that have certain desirable properties).2
As an example, consider advances in genomic sequencing. Sequence genomics has created a path for establishing the “parts list” for living cells, but to move from isolated molecular details to a comprehensive understanding of phenomena from cell growth up to the level of homeostasis is widely recog-
H. Kitano, “Systems Biology: A Brief Overview,” Science 295(5560):1662-1664, 2002.
For example, such principles might occur as the result of convergent evolution, that is, the evolution of species with different origins toward similar forms or characteristics, and an understanding of the likely ways that evolution can take to solve certain problems. Alternatively, principles might be identified that can explain the functional behavior of some specific biological system under a wide set of circumstances without necessarily being an accurate reflection of what is going on inside the system. Such principles may prove useful from the standpoint of being able to manipulate the behavior of a larger system in which the smaller system is embedded, though they may not be useful in providing a genuine understanding of the system with which they are associated.