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Goals and Approach

Peter Sorger, Ph.D.

Center for Cell Decision Processes is dedicated to advancing the interface between biology, engineering, computation, and the physical sciences. Three broad trends underlie our interest in systems biology. First, as engineers and computer scientists, we are increasingly interested in the application of numerical methods and engineering paradigms to biological processes. About half of the investigators in the CDP Center are first and foremost engineers, including Doug Lauffenburger, Scott Manalis, Jay Hahn and Klavs Jensen. Second, undergraduate and graduate students continue to push for activities at interfaces between established disciplines. Opportunities for ground-breaking research and the commercialization of new ideas are particularly rich at these interfaces. Finally, and perhaps most importantly, as experimental biologists, we increasingly perceive a need for new ways of tackling complex cellular processes such as cell-cell signaling, transcriptional regulation and cytoskeletal organization. The focus on individual genes and proteins, which has proven so powerful for the molecular genetics of the past century, is in and of itself inadequate to the task of describing dynamic processes involving interactions among tens, hundreds and even thousands of components. As a consequence, even as our understanding of the genetic basis of human disease advances at an increasing rate, the information needed to treat and ameliorate disease remains fragmentary and incomplete. In recognition of this problem, the past five years have witnessed efforts in many areas of biomedical research to build capabilities in computation and high-throughput analysis with which to tackle biology at the systems level. The hope is that systems-wide modeling of cells and organism will yield greatly improved understanding of development, physiology and disease.

In its emphasis on formal numerical models, systems biology breaks with the tradition in genetics and molecular biology of anecdotal and pictorial models. However, the experimental emphasis in is also critical because it is only through experimentation that models can be tested for their accuracy. The empirical underpinnings of systems biology distinguish it from the older field of theoretical biology; in our opinion, there is no prospect that biomedical research will become a computation-driven field any time in the future. Moreover, little will be gained if systems biology discards the chemical and biophysical rigor of molecular biology in favor of vague statements about networks and circuits. Instead, network-based views of function must be integrated with detailed mechanistic insight that chemistry to physiology. Thus, structural biologists such as Mike Yaffe and Amy Keating are critical to the CDP center’s research program.

Systems biology has three obvious intellectual antecedents: biology itself, cybernetics/systems theory and reaction engineering. Molecular biology emphasizes the mechanistic study of biological function. One of its great strengths is an ability to focus on the actions of a small number of genes without being distracted by the complex biological milieu in which they are found. Peter Sorger and David Sabatini are first and foremost molecular biologists. However, the very tendency of molecular biology to model function in terms of a series of binary interactions is a weakness when pathways become complex and many genes work together. In this case, more sophisticated network-level understanding is required. It is important to note, however, that systems biology aims to complement and not replace more traditional molecular biology. Systems biology also represents a return to the integrative perspectives and physiological interests of the 1920s and 1930s, but armed with modern technology and extensive understanding of biological chemistry.

The analysis of biological phenomena in terms of cybernetics and systems theory traces its origins to the 1940’s and has gained recent prominence. Cybernetics and systems theory played critical roles in the study of communications and computing and it is natural to draw parallels between information transfer in biology and electronics. Moreover, systems theory provides a formal framework for studying the design of biological networks in terms of error correction, feed-forward and feed-back loops, bi-fans and other canonical circuit concepts. Bruce Tidor and Tommi Jaakola are interested in these aspects of systems biology. However, the emphasis in cybernetics on organization independent of instantiation is also is a weakness with respect to biological systems. It is specific instantiations that motivate biologists, combined with a fundamental concern with chemical mechanism.

Reaction engineering has also had a major impact on current thinking about systems biology. Reaction engineers focus on the properties of complex reaction networks while maintaining interest on the properties of individual reactants. Reaction models are typically cast in terms of physiochemical networks based on ordinary or partial differential equations (ODEs and PDEs). Reaction engineering has obvious appeal in the study of biological processes given that both are founded on chemistry and physics. However, the data needed to build accurate reaction models are far less available in biological than chemical systems. In many classical applications of reaction engineering it is also possible to calculate important thermodynamic and kinetic parameters ad abnitio, something that is rarely if ever possible in biology. Even with well-understood mechanisms it is non-trivial however, to demonstrate that reaction models represent a good fit to experimental data and are sensitive to key variables without being compromised by uncertainties in network topologies; the situation in biology is likely to be much more difficult.

Looking forward, systems biology is certain to incorporate important features of molecular biology, cybernetic and reaction engineering traditions. Achieving this fusion will require the joint efforts of engineers, physical scientists and biologists. It will also be important to tackle the data drought: very little systematic data is available for good cell-based modeling. The efforts of experimental biologists and instrumentation engineers will be required to solve this problem. However, there is a good chance that systems biology will be the most effective means yet devised for applying molecular insight on fundamental cellular and organismic processes to human disease. The ability of numerical models to capture both general principals and particular instantiations seems particularly well suited to the demands of personalized medicine.

A national consensus is emerging that biomedical research needs new approaches and the CDP Center is one example of the National Institutes of Health (NIH) roadmap process. The roadmap is comprised of relatively large-scale research programs that address the perceived inability of single-investigator research projects (which represent the bulk of NIH-funded research) to tackle problems in complex biology. However we temper our enthusiasm for interdisciplinary research with the knowledge that it is usually small groups of motivated students, postdoctoral associates and faculty who drive fundamental innovation. In times of restricted science budgets it is also important that we demand of programs such as the CDP Center the same high quality and high productivity science we expect of traditional R01 grants.

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This page last modified on June 10th, 2009