Skip to main content

BALL: Biochemical Algorithms Library

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1668))

Abstract

In the next century, virtual laboratories will play a key role in biotechnology. Computer experiments will not only replace 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 objectoriented 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.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jörg Becker. Allgemeine approximative Kongruenz zweier Punktmengen im R. Master’s thesis, Universität des Saarlandes, 1995.

    Google Scholar 

  2. W. Chang, I.N. Shindyalov, C. Pu, and P.E. Bourne. Design and application of PDBLib, a C++ macromolecular class library. CABIOS, 10(6):575–586, 1994.

    Google Scholar 

  3. Wendy D. Cornell, Piotr Cieplak, Christopher I. Bayly, Ian R. Gould, Kenneth M. Merz, Jr., David M. Ferguson, David C. Spellmeyer, Thomas Fox, James W. Caldwell, and Peter A Kollman. A second generation force field for the simulation of proteins, nucleic acids and organic molecules. J. Am. Chem. Soc., 117:5179–5197, 1995.

    Article  Google Scholar 

  4. Bernard Coulange. Software reuse. Springer, London, 1997.

    MATH  Google Scholar 

  5. Andreas Fabri, Geert-Jan Giezeman, Lutz Kettner, Stefan Schirra, and Sven Schönherr. On the design of CGAL, the computational geometry algorithms library. Technical Report MPI-I-98-1-007, Max-Planck-Institut für Informatik, Saarbrücken, February 1998.

    Google Scholar 

  6. Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides. Design patterns: elements of reusable object-oriented software. Addison-Wesley, Reading, MA, 1995.

    MATH  Google Scholar 

  7. Paul J. Heffernan. Generalized approximate algorithms for point set congruence. In WADS93, 1993.

    Google Scholar 

  8. Paul J. Heffernan and Stefan Schirra. Approximate decision algorithms for point set congruence. Computational Geometry: Theory and applications, 4(3):137–156, 1994.

    Article  MathSciNet  Google Scholar 

  9. Konrad Hinsen. The Molecular Modelling Toolkit: a case study of a large scientific application in python. In Proceedings of the 6th International Python Conference, pages 29–35, San Jose, Ca., October 1997.

    Google Scholar 

  10. HyperChem release 4.5. Hypercube Inc., 1995.

    Google Scholar 

  11. Hans-Peter Lenhof. New contact measures for the protein docking problem. In Proc. of the First Annual International Conference on Computational Molecular Biology RECOMB 97, pages 182–191, 1997.

    Google Scholar 

  12. Kurt Mehlhorn, Stefan Näher, Michael Seel, and Christian Uhrig. The LEDA user manual: version 3.6. Max-Planck-Institut für Informatik, Saarbrücken, 1998.

    Google Scholar 

  13. Bertrand Meyer. Object-Oriented Software Construction. Prentice Hall PTR, New Jersey, 2nd edition, 1997.

    MATH  Google Scholar 

  14. Anthony Nicholls and Barry Honig. A rapid finite difference algorithm, utilizing successive over-relaxation to solve the poisson-boltzmann equation. J. Comput. Chem., 12(4):435–445, 1991.

    Article  Google Scholar 

  15. Wolfgang Vahrson, Klaus Hermann, Jürgen Kleffe, and Burghardt Wittig. Objectoriented sequence analysis: SCL-a C++ class library. CABIOS, 12(2):119–127, 1996.

    Google Scholar 

  16. Guido van Rossum. Python version 1.5.1. http://www.python.org.

  17. Pat Walters and Matt Stahl. BABEL version 1.6. University of Arizona.

    Google Scholar 

  18. H. J. Wolfson. Model based object recognition by ‘geometric hashing’. In Proc. 1st European Conf. Comput. Vision, pages 526–536, 1990.

    Google Scholar 

  19. Malte Zöckler and Roland Wunderling. DOC++ version 3.2. http://www.zib.de/Visual/software/doc++/.

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Boghossian, N., Kohlbacher, O., Lenhof, HP. (1999). BALL: Biochemical Algorithms Library. In: Vitter, J.S., Zaroliagis, C.D. (eds) Algorithm Engineering. WAE 1999. Lecture Notes in Computer Science, vol 1668. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48318-7_26

Download citation

  • DOI: https://doi.org/10.1007/3-540-48318-7_26

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66427-7

  • Online ISBN: 978-3-540-48318-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics