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Bioinformatics Vol. 16 no. 8 2000
Pages 665-677
© 2000 Oxford University Press

Review

A systematic approach to dynamic programming in bioinformatics

Robert Giegerich 1,

1 Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany

Received on September 10, 1999 ; revised on February 18, 2000 ; accepted on April 5, 2000

Motivation: Dynamic programming is probably the most popular programming method in bioinformatics. Sequence comparison, gene recognition, RNA structure prediction and hundreds of other problems are solved by ever new variants of dynamic programming. Currently, the development of a successful dynamic programming algorithm is a matter of experience, talent and luck. The typical matrix recurrence relations that make up a dynamic programming algorithm are intricate to construct, and difficult to implement reliably. No general problem independent guidance is available.

Results: This article introduces a systematic method for constructing dynamic programming solutions to problems in biosequence analysis. By a conceptual splitting of the algorithm into a recognition and an evaluation phase, algorithm development is simplified considerably, and correct recurrences can be derived systematically. Without additional effort, the method produces an early, executable prototype expressed in a functional programming language. The method is quite generally applicable, and, while programming effort decreases, no overhead in terms of ultimate program efficiency is incurred.

Contact: robert{at}techfak.uni-bielefeld.de

Work partially supported by a grant from the Australian National University.


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