Name
Abstract | ||
|---|---|---|
Motivation: The automatic alignment of rRNA sequences can reproduce manual expert alignments with high, but not perfect, fidelity. We examine the use of empirical methods for the identification of regions of an alignment of a new sequence with an existing large alignment which can confidently be predicted to be correctly aligned. Results: We show how to use a simple jack-knife procedure to derive an estimate of the reliability that is to be expected at each position of a large alignment of eukaryotic rRNA sequences. These reliabilities are then improved using measures that are specific to the input sequence. Regions where the sequence-specific reliability method performs particularly well are identified and seen to correspond with elements in the structure of the rRNA molecules that vary between species in the alignment. We also compare these reliability measures to an algorithmic alignment stability measure. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1093/bioinformatics/14.10.830 | BIOINFORMATICS |
Field | DocType | Volume |
Sequence alignment,Fidelity,Alignment-free sequence analysis,Ribosomal RNA,Computer science,Software,Bioinformatics,Multiple sequence alignment,Empirical research | Journal | 14 |
Issue | ISSN | Citations |
10 | 1367-4803 | 2 |
PageRank | References | Authors |
0.37 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmet A. O'brien | 1 | 32 | 5.67 |
| Desmond G. Higgins | 2 | 1263 | 383.91 |