Comparing Sequence Search Algorithms for Single Pass Identification
Author Information
Author(s): K. Cara Woodwark, Simon J. Hubbard, Stephen G. Oliver
Primary Institution: Department of Biomolecular Sciences, UMIST
Hypothesis
Does one size fit all when using sequence search algorithms for single-pass sequence identification?
Conclusion
WuBLASTn is more effective than ncbiBLASTn for identifying coding sequences in closely related species when using default parameters.
Supporting Evidence
- WuBLASTn finds longer alignments than ncbiBLASTn.
- The study used 909 sample sequences from S. bayanus.
- Different default parameters between the two algorithms affect the results.
Takeaway
This study looked at different computer programs that help scientists find similar DNA sequences. It found that one program is better at finding matches than another.
Methodology
The study compared the performance of Washington University's and NCBI's BLAST algorithms using sample sequences from S. bayanus against a database of S. cerevisiae coding regions.
Limitations
The study does not definitively identify the correct homologues until the whole genome is sequenced.
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