Computing discoveries in molecular biology
Despite companies investing billions of dollars on computer-based information systems, almost all objective economic studies find little evidence of their impact on productivity within the commercial sector. This consistent observation has been labeled the productivity paradox. In striking contrast to this is the tremendous impact databases and computational tools have had on the discovery process in molecular biology. Tens of thousands of scientific papers highlight sequence similarity results in their conclusions, and detection of significant sequence homology is often the first clue regarding the biological function of a newly discovered human disease gene. These highly effective computational applications are based on sufficiently accurate quantitative models of biological phenomena and it is the existence of these models that explains the contrast described above. I will present an overview of the productivity paradox, as well as examples of biological discoveries made possible by computers. I will then discuss lessons we can learn from the productivity paradox.