Box 9.1
On Challenge Problems

Challenge problems have a history of stimulating scientific progress. For example:

  • The U.S. High Performance Computing and Communications Program focused on problems in applied fluid dynamics, meso- to macroscale environmental modeling, ecosystem simulations, biomedical imaging and biomechanics, molecular biology, molecular design and process optimization, and cognition.1 These problem domains were selected because they drove applications needs for very high-performance computing.

  • A second example is the Text REtrieval Conference (TREC), sponsored by the National Institute of Standards and Technology, in cooperation with the National Security Agency and the Defense Advanced Research Projects Agency. The purpose of this conference is to “support research within the information retrieval community by providing the infrastructure necessary for large-scale evaluation of text retrieval methodologies…. The TREC workshop series has the following goals: to encourage research in information retrieval based on large test collections; to increase communication among industry, academia, and government by creating an open forum for the exchange of research ideas; to speed the transfer of technology from research labs into commercial products by demonstrating substantial improvements in retrieval methodologies on real-world problems; and to increase the availability of appropriate evaluation techniques for use by industry and academia, including development of new evaluation techniques more applicable to current systems.”2 TREC operates by presenting a problem in text retrieval clearly and opening it up to all takers. It makes available to the community at large all basic tools, and its structure and organization have attracted a large number of research sites.

  • Still another approach to challenge problems is to offer prizes for the accomplishment of certain well-specified tasks. For example, in aeronautics, the Kremer Prize was established in 1959 for the first human-powered flight over a specific course; this prize was awarded to Paul MacReady for the flight of the Gossamer Condor in 1977. The Kremer Prize is widely regarded as having stimulated a good deal of innovative research in human-powered flight. A similar approach was taken in cryptanalysis, in which nominal prizes were offered for the first parties to successfully decrypt certain coded messages. These prizes served to motivate the cryptanalytic community by providing considerable notoriety for the winners. On the other hand, pressures to be the first to achieve a certain result often strongly inhibit cooperation, because sharing one’s own work may eliminate the competitive advantage that one has over others.


A living cell is a remarkable package of biological molecules engaged in an elaborate and robust choreography of biological functions. Currently, however, we have very incomplete knowledge about all of the components that make up cells and how these components interact to perform those functions. Understanding how cells work is one of biology’s grand challenges. If it were possible to understand more completely how at least some of the machinery of cells works, it might be possible to anticipate the onset and effects of disease and create therapies to ameliorate those effects. If it were possible to influence precisely the metabolic operations of cells, they might be usable as highly controllable factories for the production of a variety of useful organic compounds.

However, cell biology is awash in data on cellular components and their interactions. Although such data are necessary starting points for an understanding of cellular behavior that is sufficient for prediction, control, and redesign, making sense out of the data is difficult. For example, diagrams tracing all of the interactions, activities, locations, and expression times of the proteins, metabolites, and nucleic acids involved have become so dense with lines and annotations that reasoning about their functions has become almost impossible.


Section 9.2 is based largely on A.P. Arkin, “Synthetic Cell Biology,” Current Opinion in Biotechnology 12(6):638-644, 2001.

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