Versatile and declarative dynamic programming using pair algebras.
BACKGROUND
Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes.


RESULTS
Based on this programming style, we introduce a generic product operation of scoring schemes. This leads to a remarkable variety of applications, allowing us to achieve optimizations under multiple objective functions, alternative solutions and backtracing, holistic search space analysis, ambiguity checking, and more, without additional programming effort. We demonstrate the method on several applications for RNA secondary structure prediction.


CONCLUSIONS
The product operation as introduced here adds a significant amount of flexibility to dynamic programming. It provides a versatile testbed for the development of new algorithmic ideas, which can immediately be put to practice.
Steffen
Peter
P
Faculty of Technology, Bielefeld University, Postfach 10 01 31, 33501 Bielefeld, Germany. psteffen@techfak.uni-bielefeld.de
Giegerich
Robert
R
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D008433:Mathematics; D008957:Models, Genetic; D017433:Protein Structure, Secondary; D012313:RNA / Q000737:chemistry*; D012985:Software Design
D012313:RNA