The Scientific Computing RevolutionHumanity is on the verge of a new paradigm shift to rival the changes that were unleashed by the discovery of the atom and the invention of the computer.That’s the conclusion of a distinguished panel of experts, called the 2020 Science Group, who worked together for four months to chart the future of computing.Led by Professor Stephen Emmott of Microsoft Research, the experts include more than 30 of the world’s top computer scientists, astronomers, biologists, chemists, geneticists, mathematicians, and physicists.If computing simply continued to make progress along its current path of collecting and organizing data, the consequences would be stunning. Consider that the amount of new data that the world produces doubles every year, thanks to computer science. Using computers to advance our knowledge in other areas of science will allow us to make tremendous leaps in our understanding.Computers are critical to the success of new experiments that were previously impossible. They can now crank out data in volumes that were once unthinkable. For example, the Sanger Centre at Cambridge has 150 terabytes, or 150 trillion bytes, of genomic data and it has a processing power of 2.5 teraflops. Its data on genome sequences is doubling every year, which is faster than Moore’s Law.Or consider the Large Hadron Collider that is being developed at the CERN particle-physics laboratory in Switzerland. In 2007, when it becomes operational, it will create 800 million collisions per second. This will yield several petabytes of data every year; a petabyte is a million gigabytes. The detectors on the Large Hadron Collider will produce a data flow of 1 gigabyte per second, which is enough to pack a DVD with data every five seconds.But, computers will soon be doing more than just organizing data. The future of computing, will enable us to move beyond the paradigm of gathering more and more data, at faster and faster speeds. Instead, it will add an entirely new function for digital machines that until now has been limited to humans: the analysis and interpretation of data.As the 2020 Science Group explains in their report, Towards 2020 Science,1 “An important development in science is occurring at the intersection of computer science and the sciences that has the potential to have a profound impact on science. It is a leap from the application of computing to support scientists to ‘do’ science. . . to the integration of computer science concepts, tools, and theorems into the very fabric of science. . . . [W]e believe this development represents the foundations of a new revolution in science.”They argue that this means we’re now at the dawn of a new era of science-based innovation that will surpass everything we’ve developed over the past 50 years of technology-based innovation.Ultimately, computer science will be combined with new tools and concepts in science and mathematics to create innovations that are difficult to imagine today. The 2020 Science Group envisions that this will “accelerate key breakthroughs in science and benefits to society, from understanding biology and revolutionizing medicine and healthcare, and from understanding the universe to the origin of life, and understanding and helping to protect the life-support systems of Earth on which we all depend for our survival.”Based on their analysis, we offer the following four forecasts:First, the most important implication is that computer science will revolutionize biology. According to the 2020 Science Group, biologists are starting to realize that they must think of cells and cellular systems as “information processing systems.” This is based on the striking similarities between computer process algebras and biological signaling, and the parallels between computational logic circuits and the living cell’s regulatory systems. Using this awareness as a source of inspiration, scientists are poised to discover critical new advances in biology, medicine, and biotech. For example, computer science relies on modular components and interfaces so that a flaw in one component doesn’t affect the other components, and the system can be easily changed. Biologists hope to use the understanding we’ve gained from computer science and apply it to find the interfaces and modular elements in living things, which would transform healthcare.Second, one key area of research in the next decade will focus on codification, or turning knowledge into coded data that can be shared and analyzed.Essentially, computing is the codification of the knowledge of information processing. In biology, codification will be crucial to progress. Scientists have already codified the genome, which consists of strings in a four-letter alphabet. This will lead to genotyping of individuals so that drugs can be targeted to each individual’s health problems, both to cure illnesses and to prevent diseases before they occur. The next step will be to codify the proteome, which includes strings of 20 letters. After that, researchers will attempt to codify networks of interactions at the biochemical level. Then they will work on the most difficult challenge, which will be to codify biological processes, such as cell division. Once this is accomplished, however, scientists will be able to store, search, compare, and analyze the most complex functions of living things.Third, by 2020, we will enter the era of Artificial Scientists. In other words, computers won’t just organize data from experiments.They will develop hypotheses based on observations, design experiments to test their hypotheses, and then carry out the experiments using laboratory robots. As reported in Nature,2 a laboratory robot used a Machine Learning system based on Inductive Logic Programming to choose experiments to test various hypotheses. The goal was to see what function a yeast gene performed, and the experiments would either increase or decrease its nutrients. The robot received feedback on experiments that indicated whether the yeast survived within a 24-hour period. The robot selected experiments that were 100 times cheaper to implement than it would cost to choose experiments randomly. As one of the scientists who conducted the robot study, Stephen Muggleton, explains in the Towards 2020 Science3 report, this development suggests that robots sent to explore remote locations, such as the ocean floor or the surface of another planet, will be able to send back far more information because they will be able to decide the best experiment to conduct based on the conditions they encounter.Fourth, the world will experience a period of sustained prosperity. This will be achieved as science and computer science solve problems that are keeping the world from making greater progress in several areas: developing new technologies, unraveling social crises such as poverty and hunger, eradicating diseases and aging, and removing the limits on economic growth. References List :1. To access the report “Towards 2020 Science,” visit the Microsoft website at: research.microsoft.com 2. Nature, March 30, 2006, Vol. 440, No. 7084, “Global Landscape of Protein Complexes in the Yeast Saccharomyces Cerevisiae,” by Nevan J. Krogan, Gerard Cagney, Haiyuan Yu, Gouqing Zhong, Xinghua Guo, Alexandr Ignatchenko, Joyce Li, Shuye Pu, Nira Datta, Aaron P. Tikuisis, Thanuja Punna, Jose M. Peregrin-Alvarez, Michael Shales, Xin Zhang, Michael Davey, Mark D. Robinson, Alberto Paccanaro, James E. Bray, Anthony Sheung, Bryan Beattie, Dawn P. Richards, Veronica Canadien, Atanas Lalev, Frank Mena, Peter Wong, Andrei Starostine, Myra M. Canete, James Vlasblom, Samuel Wu, Chris Orsi, Sean R. Collins, Shamanta Chandran, Robin Haw, ennifer J. Rilstone, Kiran Gandi, Natalie J. Thompson, Gabe Musso, Peter St Onge, Shaun Ghanny Mandy H.Y. Lam, Gareth Butland, Amin M. Altaf-Ul, Shigehiko Kanaya, Ali Shilatifard, Erin O’Shea, Jonathan S. Weissman, C. James Ingles, Timothy R. Hughes, John Parkinson, Mark Gerstein, Shoshana J. Wodak, Andrew Emili, and Jack F. Greenblatt. ⓒ Copyright 2006 by Nature Publishing Group. All rights reserved. 3. To access the report “Towards 2020 Science,” visit the Microsoft website at: research.microsoft.com