Expert Report

The Role of Theory in Advancing 21st Century Biology: Catalyzing Transformative Research (2008)

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Theory is an integral part of all biological research. Biologists' theoretical and conceptual frameworks inform every step of their research, affecting what experiments they do, what techniques and technologies they develop and use, and how they interpret their data. At the request of the National Science Foundation, this National Research Council report examines whether a greater emphasis on theory would be useful in advancing biology. The report concludes that theory is already an inextricable thread running throughout the practice of biology; but that explicitly giving theory equal status with other components of biological research could help catalyze transformative research that will lead to creative, dynamic, and innovative advances in our understanding of life.

Key Messages

  • Biological science can contribute to solving societal problems and to economic competitiveness.
  • Biologists in all subdisciplines use theory but rarely recognize the integral and multifaceted role that theory plays in their research and therefore devote little explicit attention to examining their theoretical and conceptual assumptions.
  • New ways of looking at the natural world often face difficulty in acceptance. Challenges to long-held theories and concepts are likely to be held to a higher standard of evidence than more conventional proposals.
  • Technological advances in arrays, high-throughput sequencing, remote sensing, miniaturization, wireless communication, high-resolution imaging, and other areas, combined with increasingly powerful computing resources and data analysis techniques, are dramatically expanding biologists' observational, experimental, and quantitative capabilities.
  • To get the most out of large and diverse data sets, these will need to be accessible and biologists will have to learn how to use them. While technology is making it increasingly cost-effective to collect huge volumes of data, the process of extracting meaningful conclusions from those data remains difficult, time-consuming, and expensive.