Name
Title | ||
|---|---|---|
Comparing best-first search and dynamic programming for optimal multiple sequence alignment |
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 and memory than DCFS for higher-dimensional problems. |
Year | Venue | Keywords |
|---|---|---|
2003 | IJCAI | character string,optimal multiple sequence alignment,important problem,bounded dynamic programming,best-first search,varying similarity,sequence alignment,different approach,computational biology,space requirement,divide-and-conquer frontier search,higher-dimensional problem,three dimensions,multiple sequence alignment,divide and conquer |
Field | DocType | Citations |
Sequence alignment,Dynamic programming,Computer science,Spacetime,Theoretical computer science,Multiple sequence alignment,Best-first search,Bounded function | Conference | 7 |
PageRank | References | Authors |
0.80 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heath Hohwald | 1 | 115 | 6.75 |
| Ignacio Thayer | 2 | 49 | 3.12 |
| Richard E. Korf | 3 | 3568 | 729.78 |