Catalyzing Inquiry at the Interface of Computing and Biology (2005) / Chapter Skim
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Executive Summary
Executive Summary
Pages 1-8
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To understand better the potential synergies at the BioComp interface and to facilitate the development of new collaborations between the scientific communities in both fields that can better exploit these synergies, the National Research Council established the Committee on Frontiers at the Interface of Computing and Biology. For simplicity, this report uses "computing" to refer to the broad domain encompassed collectively by terms such as computing, computation, modeling and simulation, computer science, computer engineering, informatics, information technology, scientific computing, and computational science.
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Such biologically oriented tools acquire, store, manage, query, and analyze biological data in a myriad of forms and in enormous volume for its complexity. These tools allow biologists to move from the study of individual phenomena to the study of phenomena in a biological context; to move across vast scales of time, space, and organizational complexity; and to utilize properties such as evolution ary conservation to ascertain functional details.
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Cyberinfrastructure -- high-end general-purpose computing centers that provide supercomputing capabilities to the community at large; well-curated data repositories that store and make avail able to all researchers large volumes and many types of biological data; digital libraries that contain the intellectual legacy of biological researchers and provide mechanisms for sharing, annotating, reviewing, and disseminating knowledge in a collaborative context; and high-speed networks that connect geographically distributed computing resources -- will become an en abling mechanism for large-scale, data-intensive biological research that is distributed over mul tiple laboratories and investigators around the world. New data acquisition technologies such as genome sequencers will enable researchers to obtain larger amounts of data of different types and at different scales, and advances in information technology and computing will play key roles in the development of these technologies.
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Rather, topics have been selected to span a space of possible problem domains, and no inferences should be made concerning the omission of any problem from this list. The problem domains discussed in this report include high-fidelity cellular modeling and simulation, the development of a synthetic cell, neural information processing and neural prosthetics, evolutionary biology, computational ecology, models that facilitate individualized medicine, a digital human on which a surgeon can operate virtually, computational theories of self-assembly and self-modification, and a theory of biological information and complexity.
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From page 5... ...
Accurate data from biological organisms impose "hard" constraints on the biologist in much the same way that results from theoretical computer science impose hard constraints on the computer scientist. A second example is that whereas computer scientists are trained to develop general solutions that give guarantees about events in terms of their worst-case performance, biologists are interested in specific solutions that relate to very particular (though voluminous)
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From page 6... ...
The committee believes that a new dawn is visible -- and just as molecular biology has become simply part of the biological sciences as a whole, so also will computational biology ultimately become simply a part of the biological sciences. In the interim, however, considerable effort will be required to build and sustain the infrastructure and to train a generation of biologists and computer scientists who can choose the right collaborators to thrive at the BioComp interface.
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From page 7... ...
Wild budget fluctuations and an unpredictable funding environment that changes goals rapidly can damage the long-term prospects of a field to produce useful and substantive knowledge. Funding levels do matter, but programs that provide steady funding in the context of broadly stated but consistent intellectual goals are more likely to yield useful results than those that do not.
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Today, the revolution lies in the application of a new set of interdisciplinary tools: computational approaches will provide the underpinning for the integration of broad disciplines in developing a quantitative systems approach, an integrative or synthetic approach to understanding the interplay of biological complexes as biological research moves up in scale. Bioinformatics provides the glue for systems biology, and computational biology provides new insights into key experimental approaches and how to tackle the challenges of nature.
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