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Author Boghossian, N. P. ♦ Kohlbacher, O. ♦ Lenhof, H. P.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2000
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Libraries ♦ Molecular modeling ♦ Rapid software prototyping
Abstract In the next century, virtual laboratories will play a key role in biotechnology. Computer experiments will not only replace some of the time-consuming and expensive real-world experiments, but they will also provide insights that cannot be obtained using "wet" experiments. The field that deals with the modeling of atoms, molecules, and their reactions is called Molecular Modeling. The advent of Life Sciences gave rise to numerous new developments in this area. However, the implementation of new simulation tools is extremely time-consuming. This is mainly due to the large amount of supporting code that is required in addition to the code necessary to implement the new idea. The only way to reduce the development time is to reuse reliable code, preferably using object-oriented approaches. We have designed and implemented BALL, the first object-oriented application framework for rapid prototyping in Molecular Modeling. By the use of the composite design pattern and polymorphism we were able to model the multitude of complex biochemical concepts in a well-structured and comprehensible class hierarchy, the BALL kernel classes. The isomorphism between the biochemical structures and the kernel classes leads to an intuitive interface. Since BALL was designed for rapid software prototyping, ease of use, extensibility, and robustness were our principal design goals. Besides the kernel classes, BALL provides fundamental components for import/export of data in various file formats, Molecular Mechanics simulations, three-dimensional visualization, and more complex ones like a numerical solver for the Poisson-Boltzmann equation.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2000-12-01
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 5

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Source: ACM Digital Library