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Memory-efficient dynamic programming backtrace and pairwise local sequence alignment

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...

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Detalles Bibliográficos
Autor principal: Newberg, Lee A.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2668612/
https://www.ncbi.nlm.nih.gov/pubmed/18558620
http://dx.doi.org/10.1093/bioinformatics/btn308
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author Newberg, Lee A.
author_facet Newberg, Lee A.
author_sort Newberg, Lee A.
collection PubMed
description 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@cs.rpi.edu Supplementary information: Supplementary data is available at Bioinformatics online.
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spelling pubmed-26686122009-04-13 Memory-efficient dynamic programming backtrace and pairwise local sequence alignment Newberg, Lee A. Bioinformatics Original Papers 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@cs.rpi.edu Supplementary information: Supplementary data is available at Bioinformatics online. Oxford University Press 2008-08-15 2008-06-16 /pmc/articles/PMC2668612/ /pubmed/18558620 http://dx.doi.org/10.1093/bioinformatics/btn308 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ 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.
spellingShingle Original Papers
Newberg, Lee A.
Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title_full Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title_fullStr Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title_full_unstemmed Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title_short Memory-efficient dynamic programming backtrace and pairwise local sequence alignment
title_sort memory-efficient dynamic programming backtrace and pairwise local sequence alignment
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2668612/
https://www.ncbi.nlm.nih.gov/pubmed/18558620
http://dx.doi.org/10.1093/bioinformatics/btn308
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