---
title: "Comparing Best-First Search and Dynamic Programming for Optimal Multiple Sequence Alignment"
authors:
  - "Heath Hohwald"
  - "Ignacio Thayer"
  - "Richard E. Korf"
doi: ""
url: "https://ijcai.org/proceedings/2003/176"
pdf: "https://ijcai.org/proceedings/2003/0176.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "1239-1244"
track: ""
keywords:
---

# Comparing Best-First Search and Dynamic Programming for Optimal Multiple Sequence Alignment

Heath Hohwald, Ignacio Thayer, Richard E. Korf

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 1239-1244.

## Abstract

Sequence alignment is an important problem in computational biology. We compare two different approaches to the problem of optimally aligning two or more character strings: bounded dynamic programming (BDP), and divide-and-conquer frontier search (DCFS). The approaches are compared in terms of time and space requirements in 2 through 5 dimensions with sequences of varying similarity and length. While BDP performs better in two and three dimensions, it consumes more time a nd memory than DCFS for higher-dimensional problems.