Name
Abstract | ||
|---|---|---|
Comparison of large, unfinished genomic sequences requires fast methods that are robust to misordering, misorientation, and duplications. A number of fast methods exist that can compute local similarities between such sequences, from which an optimal one-to-one correspondence might be desired. However, existing methods for computing such a correspondence are either too costly to run or are inappropriate for unfinished sequence. We propose an efficient method for refining a set of segment matches such that the resulting segments are of maximal size without non-identity overlaps. This resolved set of segments can be used in various ways to compute a similarity measure between any two large sequences, and hence can be used in alignment, matching, or tree construction algorithms for two or more sequences. |
Year | Venue | Keywords |
|---|---|---|
2002 | WABI | segment match refinement,local similarity,unfinished genomic sequence,large sequence,fast method,efficient method,similarity measure,optimal one-to-one correspondence,maximal size,unfinished sequence,non-identity overlap,computer science,genome sequence |
Field | DocType | Volume |
Combinatorics,Similarity measure,Computer science,Algorithm,Greedy algorithm,Priority queue,Bioinformatics,Misorientation | Conference | 2452 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-44211-1 | 6 |
PageRank | References | Authors |
1.12 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aaron L. Halpern | 1 | 55 | 14.04 |
| Daniel H. Huson | 2 | 765 | 91.20 |
| Knut Reinert | 3 | 1020 | 105.87 |