NSF & Congress
Dr. Mary E. Clutter
Assistant Director for the Biological Sciences
National Science Foundation
Before the Senate Commerce, Science and
Transportation Subcommittee on Science, Technology and Space
September 17, 1996
The biological sciences are poised to become to the 21st Century what physics has been to the 20th Century. Just as the knowledge about the structure of DNA in the 1950's led to a profound revolution in biological understanding, today we are poised to make a similar leap, in which advanced computational tools will be used to understand biological systems in all their complexity while preserving and exploiting those systems in a sustainable fashion.
- Many of society's needs are likely to be met, at least in part, by advances in computational biology. Examples of potential advances include:
- The development of better computational methods in structural biology that could result in the production of novel drugs and tools for diagnosing disease in animals and plants.
- The discovery and preservation of biodiversity and increased understanding of the biological aspects of global change through improved tools to analyze remotely sensed data.
- Improved bioremediation techniques through the application of computational biology to information on protein structures to develop "designer enzymes" that break down hazardous waste.
- The development of advances in plant genome sequencing to understand the functions of genes in agriculturally important species.
- Computational biology is the application of modern computer, mathematical, and information sciences to solve biological problems that require large scale computation and analysis. It can be described as an emerging discipline, for the computational power of computers touches deeply on every level of biological research.
- Computational biology deals with two pressing needs: (1) The management and (2) the analysis of biological information.
- Bioinformatics, the management component of computational biology, combines the fields of computer science and biology to manage the vast quantities of biological data being produced, including, for example, genomic, neuroscience, and biodiversity data.
Computational analytical tools have been very important to understanding complex biological systems. Advances in computational modeling, remote sensing, and geographic information systems have become vital to understanding ecosystem processes. Neuroscience also benefits from the use of computational tools to understand the complexity of the human nervous system.
- The Federal government has responded to the importance of computational biology through a number of programs that provide funds for research and education, particularly at academic institutions. Several major programs involve partnerships among agencies.
- An interagency program that is particularly important is the Arabidopsis thaliana Genome Sequencing Program. This partnership between the National Science Foundation, the Department of Energy, and the Department of Agriculture will produce significant benefits for basic plant research as well as for agriculture and biotechnology. It also involves international collaboration, for the U.S. program is working closely with similar endeavors in Japan, France, and the European Union.
- The National Science Foundation has been a leader in advancing computational biology through several of its programs. The Computational Biology Program supports the development of database architectures and tools needed to address the complexities and dimensions encountered in biological data. The Computational Neuroscience Program supports research that seeks to understand the computational functions of the brain and nervous system and the architecture of the neural machinery used to carry out these computations.
- Equally important is the education of a new generation of biologists who are also adept at using computational innovations. This can be achieved through interdisciplinary training programs such as NSF's Research Training Groups.
- Computational biology is part of a larger revolution that will affect how all of science is conducted. This larger revolution is being driven by the generation and use of information in all forms and in enormous quantities and requires the development of intelligent systems for gathering, storing and accessing information. This unprecedented technology-based use of information will be a driving force in not only fundamental advances in science and engineering, but also of job creation and economic growth.
See also: Hearing Summary.