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Bioinformatics Advance Access originally published online on June 16, 2008
Bioinformatics 2008 24(16):1772-1778; doi:10.1093/bioinformatics/btn308
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Memory-efficient dynamic programming backtrace and pairwise local sequence alignment

Lee A. Newberg 1,2

1Center for Bioinformatics, Wadsworth Center, New York State Department of Health, Albany, NY 12208-3425 and 2Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA


  Abstract

Motivation: A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward–backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis.

Results: Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10 000.

Availability: Sample C++-code for optimal backtrace is available in the Supplementary Materials.

Contact: leen{at}cs.rpi.edu

Supplementary information: Supplementary data is available at Bioinformatics online.

Associate Editor: Thomas Lengauer

Received on April 23, 2008; revised on June 5, 2008; accepted on June 10, 2008

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