Computer Science

Computer science originated within mathematics, mainly through mathematical logic, and through electrical engineering with the use of Boolean algebra and switching theory to describe electronic circuitry. Conversely, computer science has strongly influenced mathematics. In some cases computers have been used to help prove theorems. One example is the question of whether four colors are sufficient for coloring any planar map, called the Four Color problem. This problem remained unsolved for more than one hundred years until the Four Color Theorem was proven by Kenneth Appel and Wolfgang Haken in 1976. As part of the Appel-Haken proof that four colors are sufficient, they use a computer to investigate a large but finite number of potential counterexamples.

Computer science has an equally strong connection with engineering, and in many ways the connection is much stronger than with mathematics. Computers are now indispensable when it comes to designing and building any complex structure, from a skyscraper or submarine to a computer. CAD/CAM systems (computer-aided design/computer-aided manufacturing) rely on a combination of computer graphics, specialized algorithms, and a complex of supporting software to provide the engineer with a set of tools by which one can master the complexity involved.

In the late 1990s and early 2000s a new bond grew between the physical sciences and computer science. The fields of physics, chemistry, biology, geology, and astronomy posed grand challenge experiments, problems that require massive high-speed computations. Human-genome sequencing is one such problem. Biologists view DNA as an encoding of information needed to generate a unique organism. The international effort to sequence the 3 billion DNA letters in the human genome, accomplished on 14 April 2003, was considered by many to be one of the most ambitious scientific undertakings of all time. Computer science played a pivotal role. All of the sequence data generated by the Human Genome Project has been deposited into public databases and made freely available to scientists around the world. Assembling and interpreting this data has required new levels of coordination and collaboration of computer scientists and biologists to formulate the necessary computing algorithms, data-management approaches, and visualization systems. In short, high-performance computing has fundamentally changed the way biologists do science; parallel computing systems have enabled high-throughput genome analysis; and modern search engines are allowing access to unprecedented amounts of biological data.

Another grand challenge is the Human Brain Project. This is a broad-based effort involving neuroscientists and information scientists (computer scientists, engineers, physicists, and mathematicians). The goal is to produce new digital capabilities providing a World Wide Web (WWW)–based information management system in the form of interoperable databases and associated data management tools. Tools include graphical interfaces, information retrieval and data analysis, visualization and manipulation, and biological modeling and simulation. It is expected that the neuroscience databases will be interoperable with other databases, such as genomic and protein databases. From these two examples and many more one sees that researchers from many fields are now regarding computation as a third paradigm of scientific investigation, alongside theory and experimentation.