The Crucial Role of CS in Systems and Synthetic Biology
Biological cells, coerced to function as hardware and driven by artificial DNA, can perform such nanoscale tasks as detecting toxic substances and manufacturing new drugs.
Jacques Cohen
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From Academia to the Editorship
Communications has always had a special meaning to me since the beginning of my career, both professionally and personally. My fascination with computers started in the late 1950s when I was pursuing my doctoral degree at the University of Illinois, Urbana-Champaign. The Illiac-I was among the early computers built in the U.S. and I had the privilege to use it extensively in my dissertation.
-pdating Computer Science Education
Prepare tomorrow's practitioners to tap the growing volume of Web-available data and complex programs they cannot possibly redevelop from scratch.
Computer Science and Bioinformatics
In barely half a century computer science has grown from infancy to maturity. Employment in computer science was assured until a few years ago. Today, however, like in the 1960s, when demand for physicists waned, computer scientists are eager to explore new possibilities in promising fields. Biology and its related disciplines like bioinformatics are at the top of the list.
Can we replace costly and possibly unethical animal experiments by computer runs? Can we have computer versions of ourselves that can be used for medical experiments, reducing the danger of risky trials? I believe will have some positive answers to these questions in the centuries ahead. It is safe to infer the major role that […]
Constraint logic programming languages
Constraint Logic Programming (CLP) is an extension of Logic Programming aimed at replacing the pattern matching mechanism of unification, as used in Prolog, by a more general operation called constraint satisfaction. This aritcle provides a panoramic view of the recent work done in designing and implementing CLP languages. It also presents a summary of their theoretical foundations, discusses implementation issues, compares the major CLP languages, and suggests directions for further work.
A view of the origins and development of Prolog
Dealing with failure is easy: Work hard to improve. Success is also easy to handle: You've solved the wrong problem. Work hard to improve.
Describing Prolog by its interpretation and compilation
Since its conception, Prolog has followed a developmental course similar to the early evolution of LISP. Although the version of Prolog described here typifies that currently in use, it should be considered within the framework of language evolution.
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